{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "from torch.autograd import Variable\n",
    "import torch.nn as nn\n",
    "import torch.nn.init as init\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "import numpy as np\n",
    "from six.moves import cPickle as pickle\n",
    "from six.moves import range\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import torch.backends.cudnn as cudnn\n",
    "cudnn.benchmark = True"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "pickle_file = 'small_321_train.pickle'\n",
    "\n",
    "with open(pickle_file, 'rb') as f:\n",
    "    save = pickle.load(f)\n",
    "    train_dataset = save['small_data']\n",
    "    train_labels = save['small_target']\n",
    "    del save  # hint to help gc free up memory\n",
    "    print('train set', train_dataset.shape, train_labels.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train set (22152, 1, 64, 64) (22152, 6)\n"
     ]
    }
   ],
   "source": [
    "pickle_file = '321_bal_7384.pickle'\n",
    "\n",
    "with open(pickle_file, 'rb') as f:\n",
    "    save = pickle.load(f)\n",
    "    train_dataset = save['train_data']\n",
    "    train_labels = save['train_target']\n",
    "    del save  # hint to help gc free up memory\n",
    "    print('train set', train_dataset.shape, train_labels.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7384\n",
      "7384\n",
      "7384\n"
     ]
    }
   ],
   "source": [
    "c3 = []\n",
    "c2 = []\n",
    "c1 = []\n",
    "\n",
    "for i in range(22152):\n",
    "    categ = train_labels[i][0]\n",
    "    if(categ == 3):\n",
    "        c3.append(i)\n",
    "    elif(categ == 2):\n",
    "        c2.append(i)\n",
    "    elif(categ == 1):\n",
    "        c1.append(i)\n",
    "\n",
    "print(len(c3))\n",
    "print(len(c2))\n",
    "print(len(c1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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6J1Ve5sk2wzTvg2Wv56jr8FxV3pNPPrmlX/ayl3Wvedlll/Uf5hrks5/9bDdcH+t5bP+p\ndcfPjY0KyGfxV3/1Vy393HPPtfSXvvSlbnlf+tKXtjSf0ctf/vKWZl/utQHV73lc9Vnmp8Yy9h81\nhqk2OK8u+XfmkSl7Bj4botoGy8D7Vn28B+to3rM7XH6vfOUrF6Zv3nDDDe1BPv744+0471ONw6r9\n1jTnLPU51iHPJ6odqWfB/Nk3+XzVeFPvVY0N7GssF8cM1S6YD9NqLlHzppofTj311IhYuSbg3Pf0\n00+39DPPPNPSzz77bEvz/gjriPXINJ8fx0e2HzWu3HrrrRGxsk55n7yOKgvr4iUveUlLsz7e+MY3\nLkzfPPXUU1tlZdYqZN44nBm/M6i2znxWE623N7/zmav1H/vOauYhtb7IrKt7ZMrF46rvsF/zfFXv\nvG5mLO49VzVmZu5frfXIc889tzB98yUveUn3Jsa29Xlrkq81mTa4CCxaeReNL33pS3Mr2AofY4wx\nxhhjjDHGmCXjmCp8xv4yQdQb9forkVLXqDzUm/DMG3L16wXLRZQi6EjLpX5lJeoXJlVP6tcIlU+t\nA/UrilIrZH6N4WfVL6iqXKyzzC8s88qlfllTz/pEeYutnt08MuoPReaXygyqLTD/en/q16DMOJEZ\nh9SvieqeMr9O9c7J5JdRF2aedeZZqvuo5czUXeb4MkDVohrTFByner9Eq/FVqaeImgeV8kupujJl\nn3evSuHE+lK/xCvlGRUo89Sis/mwDMynptX8QdUNFUasa55DVB3xWarrEq4RqJ6s5VF5qGeQUV8v\nKmpszCim5qk4xipU1HVUPyUZdZJS3/XqYKyqSc3DqowZVHtUfXme4j4zhzKdqS+VT0Zto/IfUy6S\nmf8XCaWENOZExQofY4wxxhhjjDHGmCXDL3yMMcYYY4wxxhhjloxjaukimY06lYWmt9kfjylJqtpQ\njaiNBzO2r7FWr55ENLM5n7qnjBR2rPVBbYLcy09J+VV5M/YuJSdVm4HyfEo6e2VT9ZKRI6t7XVT5\n69gNHDPPrndsNdabsfmMtQWRek9qnFJ9fTWS9cym2JkNW8fUsZK3q3FQjZtjUW1snmw/M5Ysm73r\ni1/8YkvT5sMNcJV9YZ7VieM7rT/q+auNoplmefk8mT/bsWpTav6t56vNpPn8WV/KosWyZOxPrDNe\nS/XN3sbsap5XGykT9dxVX1YWMG5iTVgHrL+6iXTdeHr2+r1NwWdR4+lq7P7HEzXuZtYwmY185+Wd\nWdtlyjV2XJ1n5eexsf1bXX+sLTnTpnrnZO5zNZtDr2Yz7nn5q3pUa+TMWvd4b1p8pGzcuLGlVV2M\ntQ/O2yhbkWlTGcbmM289frxYq9b81cxDY/rJau5/Nf1xMWdZY4wxxhhjjDHGGCPxCx9jjDHGGGOM\nMcaYJeOYWrooRaLkeKxdivLtms5YqygtVdGqlMw0E61AybEoASfz5FuZKFYZi5TKU9VpJp9aZ1/r\n6D9jJW5Kbt+TFWeiMag05fsqUssikZEoKxsbmSczzUjHM30wI11W0eyUpHdMtBFFxp6q5NKqj69G\njj3vOkRF78i0aRVZT6H65jw7w1i74TLYRhgpSUXpUlYk9gE+ozp+qShWqi2oeTsTiUlZAzPRIvlM\nWR8V2pZ4zxynM7ZV1U8JP0vLk4rexfPr8WeffbZbXt4z71PZSXnfap2h6oP5q3XB008/fUia18zY\n7lV9LQOqDyh7HZnXBldjD1fzZsZepuYedf6RRojKRLQcO2Zn6kzNp/VaGatZJkrs2DFGRUwkY6Jb\nZqLmkrVqszlS3vve97Y0xz2OvU899VRLK+s0x9V6XK3/lS2eaTVXKwuv+p6mLLTzrNmZaMNkNTZJ\nNT5mtiDobYsydp2hyquOZ7ZqUKh2UPNR95+pF7VGGjtHLOYK2BhjjDHGGGOMMcZI/MLHGGOMMcYY\nY4wxZsk4blG6xtgRIlZK2SgXrvJiHlPSSHXNsZLbzM79GTl479xMhIRMhCqFKqOSIM/brX7sNTM7\ny6t7UhFJMvLX3jPOWBKUnFJdZ1GjdGVg/St7Zs/KoCLWZeqW8kXVLpW1RT3TjFSzF02nJ9OcPUf1\nKSXDVP2B9cg8VTTCnkVmrFw303ZVH1R2ElW/yrpT889E/COZCIyLyryIOBHa0kTmWRaVvSBj9VP9\nhGk+FyWJJ5TV9yzYLK+KCsVr0sLEa6oxRsHoVsoSwH7COq73wbKofnrw4MGWzsxx8yJqzpaRdi0+\n4yeffLKln3jiiZau9Z6xeGTGx0W1WBK1hsjMVUTNLZXVRAJS54y11B9pdKGxESTHnjN2zTXPPr6a\naGtHK6pXJpJnL8+xFhYy1pq21nnta1/b0hyzH3/88ZZ+9NFHW5rjHsdGWsBqPhy/M3MZxwau4ZTl\nWlm9VFRE5snjvbUAzz355JNbOrPFBVGWNbXGV+eMyV9Zroiqr4yNKnNczddsE0zXz6qyKEs3yay1\nMyz+jGuMMcYYY4wxxhhjVuAXPsYYY4wxxhhjjDFLxjG1dFG2qmTnSlZGyfrLXvaylu7t3q3kxCoy\nTCbqVUa6q2AZetJzJXnmuSoSFOtRRT7JSGqVPWQeKnqIIiORZT7qnlTEBPW8e1YY1qmSSpKxstxF\nQkXmyER6UJFf6rNj3VJCqqSn6pmraEV8tsrypNrpvPN5TEl3MzJ99dlexMHZ80877bRueSk7nmft\nVHJSJR1X0ZiUpYtWEcJxm/BZnnLKKS398pe//JC/Z+TtmSgvmfFpLaLkv8oSqayXvSgSav5i/bPN\nEWVDydiG2X9pXVJ9g2XoSaR5nxxjKOV/5plnWlqNJUouzfzZ1mkJYP4sG21RtQ54ffVM1TlqvFXz\nGWFZaJljHfA+ena3sZEzyTJbujLbFIyNUtVDzWXqmWcs+mPLNW8tlBkDSMb+pMbvTPQsotZ3Y9Zx\nmbKMjRapjqvn3ctf1bWy6KitItT8v0jcddddLc154JFHHmlpjt+053IM5GfreMtxUVmV1dyasW6p\nOWFsdKlemnMp117sF5moxZn1hzquyj4vKu/Y6FYZa5wql/p+oixrfPZsE7Vs6pmqsWRsBOxdu3Z1\nz1+R59wzjDHGGGOMMcYYY8xC4Rc+xhhjjDHGGGOMMUvGMbV0qcgzmWg6SkZVpYyU3Sm7mJKmrSZa\ngZKoUoZJ6fQrXvGKQ86hNYMWCN4z8+D9096mJGWU8Clb25FaInj/Slao5KGZXeEzO+Dzeavysp6q\nLJO79bOOqq2E50bkrG4Zi99aZzURHXppJV9U7SUj+58XPS5i5fPKjAm9PDNSeyUjz1iOFBnp+xip\n9Vjb4diIePOizKyGsZFSVISkRZWmKzKRMfhcOJZVW5KakzM2MpKxEKvP7t+/v6UZKUWN31VqzbmS\n8yPHb8K8lZ2J842KjEEbAMtOuxSfB8tZ82F+KmoK8+C6QUWfZNn5zPjclQWN6YcffrilWe/r16+P\nCN2nlN0kE/lk7Pi4FslYkdQ998bYsfaFzBo1E+1trL2rN25krpOJSDM2OlkmMmUmEu481JyfsaaN\ntXSNyX/s2i2zZl/UKF0cD/n9kGnaczknKKtsb33fi8I4i7LFK0t/xn6uLHgqMmbv+rx/1RbGRhLL\nrB3mWbdm6R1X7TgTJSwTPWyepfxw5e2NSWOtfGp7l7FRD8lyrYCNMcYYY4wxxhhjjF/4GGOMMcYY\nY4wxxiwbx9TSpcjIIBVVWqmibinLhtqpn+crWWPGTkIZoJLK9VCRTHq7fs+eTzKRdTI2mnnn8J6V\nnHY1thxlB1PPmGlK6XtRoPj3sVGqMjaeRWI1kVfYl3rROTJtS5UlYxlQEewIn7/qy73IW2OtSqrP\nkkzEDNWX1P3x/DFR9jLWVmU96EXwidDPScHP1megPqfsWiyLihCzDNH02EYzcyXrhdbhaj/i31W7\nVDYjMtYSzGe+b9++bpr0bE+0blGOv27dupZWti+mKf1XUVaeffbZlqYtau/evS194MCBluaz4fhY\n82d90a7FsjM6H+uO98RnpiKrMfoMI9TQxsV63717d0ufccYZLd2zyq0mgswykIkWqix4pNd/MtZI\nNQaoiLinn356Nx+2HVWGniV0Nv+eFUXVi6ojNSdlbFSqzjLRs+aRsUJlbGqZ/NVn5633x9qfe3lE\nzI/6uQhwrmSa7ZhpZekaY29T3z9URCsVCUpZe4iynfE+eusl3g/XBKp9ZyxdGUv9WCsU6Y2b6nuF\nur7KOxNhLBNhi3Mun2vP0sW/q8/xuFpPjI08a4WPMcYYY4wxxhhjzJJx3BQ+mV96MhuQ1Tdf6o2o\n2sBKvR1Uv1qrTSmJOke9Oa/5q7fpfGvLcvEtpNpQLKOeUGVXvxL0yqB+jVH3rzYXI+otuto4q6fM\nmE33fsnhG/iMskptTLYMv1pm1AKZdt/79VH9wjn2+WfyUW/lMyqVecoY1b/VmKE2USeqr7GtqV9F\n1a8avbauFIfqF4LML8fc/JC/NmU2FeX5PeVc5tftjAppGTZqVvWfUQuwDVLRcfDgwYjQfY2/IvE6\nSuGj+gDrn22QihkqY/bs2dPNp6fwoVpBlTGjPFLti/fE9sp65EbNVM/wV9be/Mfr8BnxPk855ZTu\nfYxVC7BuWC72XwYw4KbN6lfyivo1lSzbXEmUWmQ1qoieWoPM2+w5YmXb2bx5c0tffPHFLX3eeee1\nNPsjnzPVZ7fddltL33777S392GOPtTTbco+xG3Wr+8sogjK/7s9TJJHMmlqprzJjdUbBpOjNc2Pd\nEssW4EDVbWaNpgLa9NpGRhmj0pxnqaRV6iC1duX8pFSq9XzOX1T4qPlWzedq/TlW4U3mKXzUGjmT\nR2YMUOnMptt8fj2Fj1Lv8FkzzYAJzJuoTcIVi9+rjTHGGGOMMcYYY8wK/MLHGGOMMcYYY4wxZslY\nE5s2k3k2nIi+rIsSKUKpKiXMTJOMLUptmjTWxlSls2rD0YykV0lFFTxfbUyWoZZBWSxUHSmJX2az\nXT5jJWckypJX81SbWauNUZdto+YM6vkqaXYvrTa9U22Oz1ZZFjPH2V7UpsZKClv7r7LxEWWhUXkT\nloV9hnmq+5hnS8n0adW+1SbMPK6kwSxLr05nr9uTQVPamtlEfqyNZ1FRUnM1b7A/cKNVbuRbYf1w\nw2A+Q7VBu+pT6hxaiFgWHucczXmg2kxYLraX9evXtzSl0Jl+pCyTXEcoGTU/q/pDhXJtZYllXfN8\n3ivvSW20rcqu5mi1iXVvQ/VMcAii+uCi9s2MrSCzoXpvHanaqBqb+TwvvfTSln7d617X0ueff35L\nn3nmmd1yqW0Qdu3a1dJXX311S999990tfeutt0ZExP79+9sxbnKuLDRqXM/Y5DLrYbV5fG99k1nb\nsCzKysFxUPVxjnHKdq3orUHVHKvmh0xAl0Vd36rvZqvZTqS3lQXTagNgpjl+n3rqqS1N+6Ra/6j5\nSVl4OedXG7daE2S+U6k2oubWTHAVNVb22qDqF2Nt72o8UO8fVHtQ82kvYBDrhfM50wyMwPri9Xmd\nsRbpxZxljTHGGGOMMcYYY4zEL3yMMcYYY4wxxhhjlow1YelSEW+UfKu3mzjPVRE1KLMeGy1A7b5O\nKRulWcpCQglnPZ6RMytblCq7imLFuqGUXllh5sGyU8ZGlOxM2Xsy5/M+KEskSqJ41llnHba8SnpI\nxkZRWOuMjdCgzunJMFmHyoqlbFyMKqOsBsqeqSIdKKtVL1oO+zGllKq8auxRNhc1rijZppKfHil8\nNipKBdN8HsqKM9aO1ouyl7ESkowEflFtIwolK1fzQy+SFo+pvpCxkaloTjyf1iJG9lHRKJ988smW\n7ln21BzLcqnoKERJ0Hk+y6iiajDNPHsWnF7UsYiVsn5abtatW9fStAHwOnxmPId9lpLxjAVb2Ql6\nf1dtUJ1PFtU2krHgZ+qiZ5NTlhyuM7ds2dLSr3nNa1r61a9+dUtv2rSppRm9K7MFAedWtlPmyWhf\nV111VUSsXGvfcccdLf3hD3+4pRmRT6HW6WOjzRJlOa5s2LChpbdu3drSrDv2X56vIgeyHnlN2t1o\njav2mwg9ts5bM2ei5mUioi4qauxXdh6i+l4viqiaE5V1kGVhm2Lb4TityqjWi2wXnENrmTkf8LuT\nsj+prTEh63lEAAAgAElEQVRURMtMdDRll5oXMYv9Tq0tM983lB1O3Yc6zvzZx1mv9TkpuyfHA1V3\nfNYc/zPrXrJcK2BjjDHGGGOMMcYY4xc+xhhjjDHGGGOMMcvGmrB0kbGy+yrTopyK0nFKSyllo0Qq\nYxlQ0XeYp5JBKilblYkpqTlRlq550sPZsrO8tJyoKEJKmk6JW++aKhLAWFSkA0rmeA6vxXtlO6gy\nSkrsmM5EY1pmMlGOMpLfKndUfYTX4TkqehyPU6rKvq+k7yqSgrIJVkkt24WyOlLWyT7FMvL+lDxU\n2SNVJBa29Z4NIyOhVfJUlpf5sB9Rjs57VdFGVEQf2k/qOaxr3jNRti/VxhZVps5yqzFLRVJT6doG\nlZ2qN75ny6jy4bzM9qLmFc5JPKfmc8YZZ7Rjqo+oiFYKJVlnWSi3p82Fx9lP+Nna7vk5RkRjmlaR\nakOOWDmuEY5ftIZxrqRtoBf5bPY+elL5zDy/GqvTInG0LDG981U0NNq4rr322m6a7UWVRUWkUW1d\nWTjZx6rVi/ldfPHFLX3OOee09O/8zu+09P3339/SGXsqUWtgtY7jOMA+UPvbq171qnbsjW98Y0tv\n3Lixex1lHVLRkFQUxb1797b0DTfc0NKf+cxnWprjZm/OU3VBMtHOMvmsdTIRlEkmYmk9R61xVERa\ntjn2F2WrpdWrF/EpIrfdAM+vxzkPP/HEEy3NeyJqyxWi1hmZ7xLqPnpbp7AuVAROZdFSVnOWl+te\n1pP6fqzum3Nxz46mPqe21uC98j4y7w6IFT7GGGOMMcYYY4wxS4Zf+BhjjDHGGGOMMcYsGWva0pWJ\nBFTlTZRMUqZGWZba6VrZeZSFiHnSTqIkhLzuPLmbkkur40pCSAmaiiKk7FLMU9mx6jnq3Hl2k8PB\nsqjdzHmceVI2pyR81XZDGbuyBKg8lEVm2SIBKVRUj57sm31HRQJin2Ka8FkwQpSygFH+qSLCKSl7\nTStpbcaqQssTy8j7UFJRtk2WQUUKURHneqj7Z7nUGMdoXI888khL08qm+gzHLY6JPautuv+xEtaM\nJWCRoLRXRYVSNq1eu+NzZntSz02Nbyq6RsbmrOxgykJSYVtQUm/O87y/jK2B98o+wDx5XWX/ZJ71\nHFplaOOiTY1RumjR4X2rNQrLyL5ESxfbDM9RUUB6li6irA1qTaXsc4vEWLtaJrJi/Syfz+bNm1v6\n67/+61v67W9/e0uvX7++pTNRT1UUGj5/Ze1R9sj6rNWarEbxilg5l1x33XUtreb/zFiu2ppam155\n5ZUt/Y3f+I0REbFt27Z2TEXLVOtiVUecwzjn8/yzzz67pXft2tXSF110UUtff/31LU0bXM1TjZ/K\n6qbm00W1cREV/SnTZ+dFQ1NzVua7jlof8XxlS85EhVRbBtQ5h22Rc6VaF6otGdQcrizaysalLF28\nv2r751zJOUvZ3jJrIc7tXMeyXJn1rYps2ttiIWOfVxE41T1lODG+nRpjjDHGGGOMMcacQPiFjzHG\nGGOMMcYYY8ySsSYsXcqipKI+9KSdykpBiV3GJkGU9JISMGWXomRbSfvqcWXdykTZUeVVZaQETO0Q\nr6xvvL9efkoyR0mgkgKrCAGqvEyrSCwsA4/37Ax8XiqCG1GWpkVFSaGJkqsqqWJtL4xYoyJXUTLJ\ntJKNqig4vD6fOdsu7WBsI72IXRwzVNtSYw8tT6o/Knko60ZF8SFKel5RcnjWl4p0+Nhjj7X0vn37\nWpqSfGVZU/XLsZ2frXW8bt26doxRvNjXlW2EqPazSCgptIpModoRn2+1/6hIhsq+kLE/q2gfKsII\nrUgqOlyvPJybOIezvbCOlHyd5VXzCtO8lrKGqz5W64D5KXsXLV20YhE1b7KuWV5axnivrDOm2WZ6\nqLapIi2pNdWiWroy86ay0yibSc2Hf7/sssta+i1veUtLM5Kbqk9lsVRrStUflB2P9MZY9kH2l0su\nuaSlt27d2tK33HJLt+wZm5pa87Ft0jpFi9l55513yOdU+85EglRzktrigccZzYx2PtbTr/3ar7X0\n7t27DymLsuVm1rSZKHuLyrwIXBHzbZCq/asIUTyuttVQ21eo6E6q3an7q2kV9VNZocZGAFV2ONWX\niJq36lyo5kTOoaq+1HdSft/gmjbzPVt9/+19J1T2L7aN3vfU2fxUOoMVPsYYY4wxxhhjjDFLhl/4\nGGOMMcYYY4wxxiwZa8LSRcZGOapyKMqpGKWLsi9l/VESsIz0jZJnJTnNRDapZHbgZllUpCNli2HZ\nVZQfHlcy/HpdFSFJyRl5z0oiq2TfKsqPKqOS81cLAeuIUnolN1QS7GWwdGWiXqh7VrLJ2jeU5Yn1\nT5sV+69qR5Rksg3yfD5H9g22BSWtrPVByTw/x/ukDFRZulR0sp5NktePWFl/tN2oyFzzxlBlv1H2\nH97Hww8/3C1LRmLPNMvI+qiS/40bN7ZjfAaZdkqWLUqXisyhLERqfqjtju2vFy0tYuU4quZBoqIs\nqsiNbEcsYy+6VcTzdUDrkbJr83M8riKPqPmG+avr0q6inkGtS1Uu5k2ZOs9RkXg4DrN+1Wd5f7RQ\nUjbP8WzeuKLao7Ktsrysj0VCrW2ULUpF9OzVLdsWIzWde+653bIoCw/J2FZUudR6dF70KpaLY8mm\nTZtamvd32223tXRmbaWeAdO81lvf+taWvuCCC1q6jgm8T/YdNWeNtSaqcVDZ53hdWtDuueeelt67\nd29ErBxLScbStZrIcmsdtV5Vtihlg5zXHlUdqjw4P3LNpeZiNVepKJ20S9f1tvrOqr6/ZcYMtZ2H\nitKlxnsV3a+Ohfw+z3mK8ybX6WorFhW9m+VV3zGU/VVZsGoZMtsq8HPqO4MtXcYYY4wxxhhjjDGm\n4Rc+xhhjjDHGGGOMMUvGmrN0jZUP1vMpkaJVhPIuZU9RUCbHfHh8bHl7Uk0lEVNSOhUhiZI1Zbeg\nlI73RDm62k1dyU97ZVeSQCV5VFJvyuqUHSwTDYHy6Fo3lDtS4kfbhNotX0l3l0H+SuZFK5hN9yxC\n7I+0J9EKdfDgwW5aSRaV3FFZutiO1PPtyUlZRspG+Tna0dT9ZWw2SprO+uN9MB8+gzERb+ZFWItY\nabHbv39/9/rKEqrky6Rnj+M9q7amJM2ZSIeLipLmq2c3zyKs5kQVoUpZypSdSFl1mWb7Uv2B81Yd\ny2nDpSWJVijOa6pcyqqiIn+wjLSKMJqd6u+1DCwX5ybeE4+z3jnPK8k8749lpySe59NCyahAHG/q\n854XdXQ2reqXLKotWq1n5q2VDkdt61u2bGnHtm3b1tLqOavnkokcpKI8qmg9pBe9U/Uvjhnss5df\nfnlLf/jDH25prgVU+1LrZK5vr7zyypZ+3ete19LsD7UNqjFW2ZPVvK1sWWoOY5rjA+Fzuvrqq1v6\nxhtvjIiIT3/6093PZa45xm64CMyLmjSLstT1LIuZPqVQa5KxabX9CMfsnk2/F61z9tyMRYtp9R1A\njR9q7UrY7ur8R4ul+v6q+o4aM1gf6nulahuq//TWRsqKpbaqUFsssO7GWqEXsycbY4wxxhhjjDHG\nGIlf+BhjjDHGGGOMMcYsGWvO0pWhJ6NSu51TOqXkWkq+15OqzuajpPQqOkkPJZlkudRO7er6ygrF\n+1MyOCVR7NkmMtL4sVJFFXFN2UZ4nBJC1hnlfxXWkdq1nfkp29syWEUycnCidpxnukoPWc8Ze5ey\nRqhIB0pyqnbfpwyyZ1mIeN6+xTJS/qrGG57PNMvei2QWoaWdPIdp5tOLxKfk5ZmIFcrSxedE2B8z\nkRyUbbO2DyUvVnL0TOSNRbWNEDVOZupCzWEVZd1SkbnU/KjaEdO0HDPNNq2iVNU07U+M2MHjLDv7\nDsch9mveE+cMloU2EF6Llk8ld6/5s7/07m32+ioyqIrswnpUdnTmybIzKt6BAwdaurYJ1qnKT9nU\nlYV03hpprZJZO/J4xtJe28CFF17Yju3YsaObH1G2A2X94FjOiE98Xuecc05Ln3XWWS2t+n7vOmrd\nzXZESyHboppvVJ2yXIxmRhvX1q1bu3nWOstsq6Da62rsxGoMV1F5OQ7VKGd33HFHO8Yxbiwq2tki\nkanzjF2t19ZU++OYpupNrZeJijbMdGZrkV57VFFiM+O0WsOpdcZY+69qdzWtxp3MeJv5vqnsaGo9\nrtaUvfFBjcOqftUaQp2TwQofY4wxxhhjjDHGmCXDL3yMMcYYY4wxxhhjloxjqqNVsjMl/81EOqhS\nJxUBRknEMrIvSpRVFBxKt2gL4n3wsz2pl5L1qeOUcTFCkLJxUZ5PybiSHPK+lXS1PjOey+tkpJLq\nHMrIaYth1AoVPYx1xufRu1dK83guJfCq/SyDjYtkZOJKjq4i0tT2qKJY8Tjlx0qyqCSn6pmr8lIW\nq6J31TbAdqZsICrKkLLcqOgohJ9lGTnOzbNe8pr8nDrO+9i3b19LM1IK+wzHEkYU4nHWGT+r7qPe\nq4okQRk7n5eS26voUYuEkvOqSA9KXs1xrT4jtoX169e3NOt2rI2LfYBtiu3o0UcfbWk+a5aHfYOW\nqmqjOuOMM7pl53Hy0EMPtTTnGFrKVPQsWsZoOVF2LGWfq/nTCsby8jjzU2sR2l/Z19g2VNlV2+D5\nPRtzJpoPy0s4P6jxeZFQkd9UhBc1n/J4fe6Mlsa2mNkCQK1V2Nc++MEPtvRv//ZvtzTnmze/+c0t\n/V3f9V0tzTbSi1il2r8ap1REsvvvvz/mwTw5t+/cubOlq+UpYmW/4lg1L2quskJnosqq55dZU6ln\nybG1Po8LLrigHWPELtXWSMZuuEhk5i2iLEK9OTdjq1Hf+5hW9kFen/ehLF1ERZ6taRXxWdnlM9uc\nkMx3bt6HirbVsyJn5h4VQS1jc1XRxlinKkom1yu99qO2Ghi7bcZq5k0rfIwxxhhjjDHGGGOWDL/w\nMcYYY4wxxhhjjFky1kRoBCUNz9iCeucqybWKIkFU1AUll2WaUi8Fz6+SMbXTtyojpWaUdVLqRTkc\n5aSUxmciY6idzWvZlNw0U7/qHEr/af1QUbpYH8oqwvPrdVWEEyXTI7zmMjBW5qv6Rm9ne8qmaTtQ\n9ifVpjKRCFRUIGU3VLao2mf4OVqL2EaV5UlFKlFRS5SEU0Xf4fkc22o6ExWAUlXeB+0vHGOU5ZW2\nFCVf532wLnsRIVREJ57LZ0NUv19UlEWNz47wGXH84jOqz455MwoP59BMRBq2S1o1H3jggZa+9957\nu8czYynHhDqHrVu3rh3jvbFdsI5oI3v44YdbmmMSLYO0mRDWKeuJcyv7AOuplpNRiZjm9dl22R9U\n/bL/Kpm8yl+dw/uodcn+qKIGqvFG2Z4W1W6prHaZiE5K1l/b1LxoUrN5q3mNx2kBpOVn79693fw/\n85nPtPS1117b0mwjPdusWh8oexfX6RyHmLeybbAe2QfPPvvslub4wHzYB2qdZaJJcv668cYbW/pT\nn/pU9HjDG97Q0tdcc01Lc/zgWKXsJyx7zwZ/3nnntWO33357S9NKr9YFvSi8EcvRN9UWEJl7U5bM\nytiISyxXJhqpsmDxnuatBSOev1dVF2p9TTIRtZQ1jWnON5yv2X85h/W+h2WioBH1HNVYkonwpfpp\nz/qW2RJkbOTZzDMjVvgYY4wxxhhjjDHGLBl+4WOMMcYYY4wxxhizZBxTS5eSKGUkqiqfej6lYIzY\nwWgCKnJEZpd1oixoStqn8qn3oXYb79mQIlbKSSkDVZYnyuconaVMjvmoiD58NvVaSuKnrFsZCZqy\nyal6pMScsnLKZfnsa73TUqSivCm7kGozi0qmrSsJpZJz1npWUncV7Y4ouyNR1hJ1XMnte/YfFaWD\nUtxMO2JfU7v5q8gfyvalZKnzrLDMm/enrJEcG3pjb8TKMYZjMZ8Bxy2e35M+syyqrykJumKs/HWt\noKw9mXmL9cz6qhGAKJvmeKnmTTVvsyy0D9x5550tfdNNN7X0gw8+OPc+eK+8Vm1ftEIxuhWfM/sp\ny/XII4+0NOePjBWF/VdFwKLdjPe3YcOGiFgZiYjWMdpZ1JzPCHp33XVX9/iOHTtaevv27S3N5817\nZb9mGWjdqfnT/kPbDO1fbDPK6s465bpkkTjSLQgi9HhU+7uK+pbJT63F2Nb5HFUfpAWMbW3Xrl2H\nvZaK2KbWAjyH/StjDWQ74txzzjnndI/PW4+o9T3PpX3y+uuvb+mPf/zjh+QXsXIc5DhBq5daD6n1\nFZ9BHedvvvnmdow2Ntq/WL+ZqHGLGk1P2YnGRpfqna8iZCoyEd5UVCi1Bs2sBXv3pNrT2OeciTar\n6lHZ7ZgP1z29sq+Go9Wmx9SfsoiRzDsSlWcGK3yMMcYYY4wxxhhjlgy/8DHGGGOMMcYYY4xZMo5b\nlK5M9J9MVJ4q81RWJUqSlVRT7a6dsbn0IsxE6GgUPQuYkgWrNK9J2TslcEzT6tXbtV2VK2L+buZK\nCqzKrlDtgRFJKEdWknlV15S0VokkJf6bNm3q5sG8lS1omWEbYZtSktae5FLlQXsBn7+KPsTnQhsV\nn4uyhLIP0ObCstGSUPNRNideX0V7U9fnffP6vG8lWVf0xrOxMuKMdFhFYGCd0l6jnpmypdbrKlup\nstxkWFRpupJLE2V95Gd7z4hWB86hbKOZeZPH2R9oM7rnnntamuM64fNVtuhaNrYzNZYwDxX5jW2R\n/Zeo+Yz1p/oA55l6nHYLppkfy6usaQcOHGhpRtbjfMY6ZRnZNvjM2A6YrnXGaGcsC+uRY4Oan+fZ\naReBsZZjFRWH5zz++OMRsTICG+07XPuoMZvXYTvav39/S6sIr0R9lu2RbaqWgevMsVYGtZ5QNmee\nw3mWWzuwPJyHetdlW1R25j179rQ0n5OybtdnGhHxuc99rqUvu+yyluY4oCIwsW44xlSbmLJmsoyZ\nKD+LOlcStZWEajtqbOq1O5WfSmciQam5im1QRZBTc3Rv7FFbBKi8M+uszBqVsN7nRRVjedQ6VtVp\nxnKV2Roh8x12XvSusetVZZlX1r8MVvgYY4wxxhhjjDHGLBl+4WOMMcYYY4wxxhizZBxTS9fYKAZK\n/kqq1IlSTsqQKTdVUC6lJKTKoqWkVvwsZWqU6tV7UlIwFUWD0mnKUylrV9JSJeFTdaCiBVTGSsoU\nqn5pxaKUnBEYeru5z+ZJ6XuVMjNv1jufl7IVHK3d4tcKqm/y+auoSPPksspeqOqTbYp9udd3IlY+\nIxWViNF0KPXm+b0oRbwO2wutDEzzHFrE2DeVdFtF+xorJ+1JSJU1jVYOll3ZXJgnxxVaUSglZ/3y\nWqwz2ntqOXl9ZZvgPS1bfyRKap6JzKGsgTWdiYqpypKRfStZsor2puyfHDdqu1P2JDWXZOTr6p6U\nPJ/X5X1wDumNj5nohxkro5qfxtrEM22sZ+POWNozEQcXFbbRjH0gc881gtwnPvGJdoz2HY6NbH+c\nYziHct10++23tzTnGzVmMB+m1bq6fla1J2XvUtFQ1VpUjWssl1prKGr75TVZv2zHDz/8cEtzLlOR\ngNmPaHPlZ2nVG7OdRcTzdVCjAEasXM8oS5Gql8zWGmsdFRVKRYgi8+zwmfmWqONjIzGp7QuI2hqg\nN/eoeUWN2apfs1wcn9hGOYZx3OS2K2yzve8bXEMyj8x3E9Wv1Zih2oyKcqcseb1o3Cy7+v6k8lOR\niDNY4WOMMcYYY4wxxhizZPiFjzHGGGOMMcYYY8yScUwtXRnJMVGy557EX0WMUZI1JWtUsm91voom\nQygT69nElEyTUMZ18ODBllaRq5TcLRNJLCPn7D0D9XwpgVO7yRPK53jftGVRNsj6Vbvr0zayd+/e\niFj57FhGZcEba0lcJJTkV52TsdDU50JbFu1MfG7KNsT2Sgl6JloBnyktXbQcUULKdD2H8lhen/Yn\n9kG2F+bH/qgsXUoeStSz6cmOM1YoFa1IyUaVTFo9Y943o8KoKFC9+1Hjs4rssmwo66MajzKS/dqu\n2e+UtFhZrjKybyWdpjQ7E7mpl87YopTlajXtJRP9hfSiYarxK3NNZbNVdhI1L2fk4Ly/eq2x82Cm\n/2bqYC1C2y7HzEwkJBUltfbJm266qR2rNq+IlbYdXp+2WrYvjs33339/t1y9SFsRej2lbFd1XFHb\nIajjPQtEhG5ryrbBNYWyD6qtEmrZ+RxpueJYyahbCmWp5ppCzbPKSjZvaws1fqrnqLbNWE00zLWI\nsgYqW5R6dvPqIvP9Zizznvks86zWma1SFMoCzjpS63SOT2zfagsWlrPmz36s5nbCOVGtXVXbUPO8\nso+pLV3qOfycsoWRjB1+rC16eb/BGmOMMcYYY4wxxpyg+IWPMcYYY4wxxhhjzJJxTC1dJCOFHiMd\nVueq6FNKTqsiLaid0plWEnMlN691kNlBn9aL/fv3tzTlc0Rdk+VV52ckuLXMlI0qWe6YiE6zefIc\nFRlJyVXV8fvuuy8iVkoMeU1FRnp3IqKeaZUt0tqkZKCq7VBGzfZH6Sf7AM/h82UkAFofebwXLYD2\nSbVrPsvIc9Su/JThs43S5qJk55noQj2pL/NjvfOaHGN4T0RFLqBFi2miIiCMGeeXIbLPalBy9IzV\nj9QxS0X9UJ/LyJ+Jsnqp8qpIGuw/9biymimrcsYekom0pGxUKlrkvChdisw9qfIq65bKJ2MTq+eP\nkbHPnqMsD4s6h3L8VHVLMpaP2o5Yb/fee29L33333d1rqshVtDMre6jq+2effXZL79y5s6WVdaqm\naVui/Zl5s+64pn3ssce6ZVT3yjxpteIWALwPzt2MtlXz4bjD+mJ51ZojE+U3Y2XMzHO99biKupnZ\nvoFkvp+tdcaWW80Vve9nakxVqOeficyV2WIhkx6D+t7ciww3ex1ll1LbZhA1J9SxkJ/jGlXNvWqu\nVBbLzJqa44eKUj1vbaaee8ZimbHsKxazJxtjjDHGGGOMMcYYyXFT+Bwteps1qc3zMm981dtUvuHj\nW3S+7VO/kqnNl2p5Mm9zuaEqf4knGQWT+mWCv8qrX356G1fx76yLzJtrwnzUJl7cuJCbD1IxwbfI\n3KiZn61pbt7LN8TqVxe1+fUykPmFIPPLVE/1QeUM21lmI0P+YsdNf4lS0qgNmU877bSWXr9+fUuz\nnLUdsR3znpXKj2nWHds0y8L8M5vjso/xWmyP9bj6FYqf468kTHOcYD58vmpDXrXh5JGqejJKAPXL\n+TJs5qyUkOqelXKjp8ZQvzaqeh77y29m48HMhvHzNlzO/MqaUWiqfNSvv2pjabb1nmJGqaPUukGl\nWadMq3GLqPUC+28v4ALHao4ZPK4UhZlNUhcJ3vM8JXeEHpt6fUD98qzyJnwuNUhFhG5fhHPVOeec\n09Kvec1rWpob8/NaNX8qgNTakp9TG+OqtSjh+VzzcY3I+5j3qzzLyzUB192sI56vxmHWB8/hun7s\nvNX73sD10qOPPtr9nAq+ocbhRVXVZuowowBV51eOllJxNfWc+Wwte2ZzbqVIUt8rVZviPKgU3irP\nntKffVeNMRl3iSKj8Bnr8DnarKZvWuFjjDHGGGOMMcYYs2T4hY8xxhhjjDHGGGPMknFMLV0Z+dxY\n21XvfFqu1KZvGemdknQpS5eSdKvNaasMTUkp1QZ3PM5rKsuR2tSOElVucMtNbWl/4T3VcqoNazOS\nciWBozyP5brtttu66S1btnTLzs0Nb7755kPKQ7mu2gxMyYvJWNvgWkTZQ5T1QvUfWgCq7Jl5s40o\nawDTbPfK8qTsCLT6sR2ptq42t+wdY73wPtSmzZSf0v7EfDLPQNngWGe1PtgulfVDbT6d2dx93qa6\ns3lmqPc6Vhq9DBvAKjL3k7HQ8rnX4z2bbsTKtpWx0WVsWUpSnbEl9fqDmp/VeDPWGkfU2kVtYq6s\nKPV4ZmPJ3qass6i6zqx1Mps29wIosE7ZvzmW8P6UNWnZ+uzYfqKo9Zuxcak5WZVF2e4491144YUt\n/YY3vKGluc5i++qtC2kJZnvi2o7zxF133dXSu3fvbmllkVZ9g/fNeXbbtm3Ro2dJVH2K90lLl6p3\nns91xo4dO7r50N6lxgRlLann0L7HtX5mnCDL1jfJ2P74tSSzuX4mrfIkvXvNzCvqO6laj7Nf85xM\n0A61rq79lOeqbSAUaq2TsV9ltnNQ8/8YVL2P/W6tWMxvp8YYY4wxxhhjjDFG4hc+xhhjjDHGGGOM\nMUvGcYvSpSTSmV2ne3JOFYUmY2tQeasoOM8880xL03KycePGlqYUmlJnpqvklPIvdU1eh5KunuQ6\nQtuSnnzyyZZm5CrKP1lGyuAoS513HZZdSXGVjJxSXEZR4mfvu+++lqZ1i/d30003dc+p8l71vJSN\nKBPhYlGjdykrmnqm6rOso2qpopSTeahIUMqGwXZE+SSfHdsOI4moKF2UsjNd5dVsc5kIWTxfRStQ\nEeF60vjZaykZK4/XfJRVhWll6crYMJVFRkUgIvMiIKioLYrMOYtqt1RkrFDKTlzbl2q7KroXLQiK\nsZYu1ffVfdS2rqTVhPkpC6JqryqdGYeUxbEXpUtFIFMRfzLRVDJ2IDVuqyhdtY+raH48zs+tZj22\n1lFbBmSivSnqOSp6DVH1ybXa61//+pamjZ3jwc6dO1v6qquuamnaj9SWAcpmUVFRJrnm/NSnPtXS\n+/bta2n2L67LlG2TMEpXb909m09dp6j1Kp8BI7z2oglF6CiWb3rTm1r68ssvb2k156nvAYxIViOY\n3nPPPd1z1diu2piyji0San2SWavM22ZDtYtM21GWnExa5ZmZt3o2brVGVd/r1PWZD+c+tZUB+waZ\nZ+nidVRU6LFR/npRNCNyW62wb8zbPibTZtQ4r9qMo3QZY4wxxhhjjDHGnOD4hY8xxhhjjDHGGGPM\nknHcLF1E7dKdkSvVz2Z2q85EiMhIqiglY55qp3Ilaa15qh29M9EwGImIKLsMj9P+pCxrSgpaoy0o\nmdkubVoAACAASURBVC/JyBOVrG3Dhg0tTZnyHXfc0dKf//znW5pSW0Z74L1WS8/WrVvbMcoNH330\n0UPOjdCSveO90//RRlkslbST51POWWFfUBFblCxcRY5S7ZLPkdG4KC1V1g5+tl6XfY1RNFS5xlom\neB+8PtPss0wri1lN85rqOSpbmJILZ8Zk9hPWh5Lr9u5DlSUzfigWtZ9mIraoqIzKDlDrV81TPK7s\nG2MZ+9l5keqUVVpZb1X0KRVVREn81fF5kbl4XOUxth2rMVmRkf6reqrX5Zihoiuq9RLHtWWIBKTq\nP2NfJD3LCY+NXVvRrv4t3/ItLc2oW3yOnB/VFgPKftyL3KOitPE+aOO68cYbWzrTvtXYUK1NESsj\nsz744IMtfdFFF3U/W/uA6pusoyuuuKKlWae8D65dL7nkkpbmupPXUjaXMZEA2b8yttGMvWcZUJEV\nldVr3vicWYeo+U5ZPzNWr8x4P2+ezUSrXM2cxPpVli413qjvynVuYR/JREVUlmv1XT0TPVM9A45t\nve/06vuOajOZCG5j500rfIwxxhhjjDHGGGOWDL/wMcYYY4wxxhhjjFkyjqmlK7ODeSbSQY/MuZmd\n0lU+PJ/SeBUFhNIstZN3PUfVBfPmjvy0J9G2QrtHtVxFaFkbz2H+Bw4c6JaB+Zx//vkRsVKm9/TT\nT7c0ZbxKGse0kpAychKluIzAQBkt8+F1t2zZckiaUZwoec3YA5cZJalWkddUutapkoKrXfPnyTpn\ny8IyMn+2b6YzEWlqnpmoWDyupNPs9ywLP6v6KVGRPFQ0poqS+SorkDpHWa3UuKksMirqQR1bOZZl\n7AyLatfKwHtTz0LZJtguWKfVnqjy5rjes2xE6EgTYyKGHO4c0rN0KXsjYRnZv5XFU1kiVLmUFWqe\nDUPZv9T4kZH1q3NU2Xtj9Wx5e3J3ZelS9h+eoyzgizrnqjat5sTMOrXWReYZsg5Zt4xKyXWOsjWo\n9aqaZ5WVoVd2rpf37NnT0tdff31L03KlLMGZOuXxO++8s6U/9KEPtTTXgj3rqoq0yfSrXvWqlv7h\nH/7hlub2AiwL166bN28+5JqzqPFURRir4x/X4GrcJmpNp8a1RWXs/KTu/0jHqYw9aGz6SFHrUtXv\nMiibmJpL1Hdltb7p9ZPM+lPdq+rjY9cumXcK8z5HMt+VVzNXWuFjjDHGGGOMMcYYs2T4hY8xxhhj\njDHGGGPMknFMtXpKlkrJL6XWREXlqVIvZY3IyOEo++pFu4lYGaHn4MGD3XNor2J5M1G1elDStm/f\nvu71169f39K0Yp199tktzehWlNLRLvXII4+09G233dbSjIZ1yimntPT27dsjYqW8jHVEaamKRKAk\n8yqSx+WXX97St99+e0t/9KMfbem9e/e29Nve9raWvvbaa1v64osvjggtS6blRkU7432oqG2LBO+N\nEkclU8xYl3p5KKmoiobFNKXhTPOzSoLOvpSJdFWPZyxdmXFFyUaVxU1ZHJUNoleGTHStjEQ4YxtR\nZM7pRaRQz3GsPWLZUG1ajUE8riI09uDcMHZMy9ifMhHsSM++yHUD60L1HWXp4pzMsb8XoSoiF5Vl\nni0qY1shX+u2rp5Hbzxnm1K2QqLWd2MjjK1FVFQVkpHy92zUqt+p9sI2x+ii7Mtq/FBzfsZKwOM1\nwivXf1yv/uEf/mFLf+ITn+heX/XfjDWRZeE2BR/84AdbeufOnS3NCFs9VD9lHXGtXdfFs+eQzLYV\nmYhJzL/W8d13392OqeiKY8eY1URmXOsoS9O88Vmt59R6Wdkz1ZYJTKv2MnbM7EWhy9ipx0ZmVREw\n1XYbREUnq2kVuVDZUDORuRUZ65uqv559bOx6ObPWHd0GRp1tjDHGGGOMMcYYY9Y8fuFjjDHGGGOM\nMcYYs2QctyhdZKwsiXKpKtlSErGxMi5KwJQEnvIxJRNXciwV5aQH86AsmjYXJSOjrE5ZpFT0BlrD\nHnjggZam7euJJ56ICB1FiceVRFzJTDPRzlTUJZ7Pe2LUipq/ip7Wa18RuagZywDvU1m3iJIc13pU\ntr/HHnuspR9++OGWZgQ2nkMbF/sj+xel5MyHclLaIFneKkePeF4WquwxSi6t5OiUz1NqzjGD0ntl\nueHx2gcjIrZu3drS1aKixg+2e9UH1TilogvxvllnfB4sO4+zLqttlGOTkgJzDOCYoeS9ixrJi+1b\nRWNTz1dZGWsbVJaNjRs3do9nItgQNd6z7bAP9CJazd5THUM4HqgIUapv0n7N8zlPqIhdKlIeUf2k\nZ+kaO5eoZ0BUW1dzmHqWvfGfebANMq3GHmWFPRrRZ44HY2X6GWttbY/KvqMsheq5KCs627FCWcb4\nWZanPt/9+/e3Y+9///tb+iMf+UhLs11k2rG6b7VeY/vm2vUDH/hAS59++uktvWPHjojQW0IwP3Ud\n1ktmvlGWUHUO64BrqboNw7333tuOZSL+ZSKfLcNaN2O9ydjeemTaYgZl/czkMyZilRoziLJOjbVC\nqTViJiJY71qZczNRtBSqnajv+YqepUv1wdVgS5cxxhhjjDHGGGPMCY5f+BhjjDHGGGOMMcYsGcfU\n0kUykSnGSL0oHVMydRVFQsnLKJl89NFHu9ei9UBJ5ZTMb97u3ZTA0Z7E/ChBpwyfUMqvJKeMwLVh\nw4aWpvT98ccfb+mHHnooIlbaY5REOCOFzUSJolyVz+P8889v6SrLjVhZH3v27GnpKtXvRU+ZvSbr\nXUVeW1SrCFERnXhvrIsxUkllzaC1iZE8aCmk9Yd1TvsV+yPzZLunLJXX4nFeq9qilB2Bn2M/ZVpF\ngWPZeb6KFkQ4JvH++JzqZ3tRPCK0pFtZI5XdQ1mteK8sI8cPPieWs443lNormxwtN+zLavxfhn6q\nIlMouyGP0wJV26CSQiu71Fgyli6OK8o+wHvqWbrYzpgfUTYy3jf7IM/hZ5Vdhij5es3naNkkVP8d\n29aVjasHn4UaE4lqm2RRo1vOs08cjnl2nkxklrGWLtKzHcyer9bpyipZ16NnnXVWO3beeee1NCPG\n1jXkbH4Zm1HmeCYSH8+padaL+s6g5huSia6UscJy/FXbTNSotRwTx44BGdvgIqGey7wohIdjns0o\nY7HJRNrK2JIy1+r1K5W3skWr89U6KxNdUPV3ZccfY11Sa6Sxdku2E7V2IGrcrPeq2slq7MxjP2uF\njzHGGGOMMcYYY8yS4Rc+xhhjjDHGGGOMMUvGcbN0kYxcS0nJepI8JdNTUjOVNy0ItJlQMk6JKj9L\n6aW6vyoxo2yUFiplmVDXpxWLsjbaJ5QMj3medtpp3TLs27fvkDStF6p+eVzt+K4iyzC6Qo1EELHS\n0rVly5aWpsWMdjtKXWuePFfZcijlYx6sR2XjWSQycumM7L4n1cxYgtj+aC9knbPtKDm6iqrGNsXo\nVowCRqlmtXdxDBgrp1V2ItW+VLQHlVYS2XrO2EgbSuaq+mZG6js2ekK9lmprynqZiSSxqJGAVMQ0\nJX9W4y3tifMsXbQOqqhUyvqjIl0oKb2ar5UNsvZN9mOWV9khacPgGKNslbQMjo38oebuWgeZKCUZ\nuX8m+gxR55N5EcSUpUtZ/3i+kukvat9U41TGtjHPFpSJ6KXWwnwutP6oNZ96LmosUXNb7Xvnnntu\nO7Zr166W5prsPe95T0tzbanqRa1LVCRGjgNXXnllS3/bt31bS+/cubOla59V2w6ouVptJ6Ha9Goi\nc3E9dOedd7b0TTfddEjZM2uFeTaUZSHzXDJzUq2XjK2SZI5nLIBqnTNmPslEA8v0dWX7yox9Y6n1\nrrYdIOqe1FitIu5moorynHkRKMdGwVWsZq5crl5tjDHGGGOMMcYYY/zCxxhjjDHGGGOMMWbZOKaW\nrjGRfSJy1oCaVlIsZfFQ5aIsi3YOymK3b9/e0pSo8rO8LiWqlHLV8ymFzsh4KSmjpYppll1FlGKa\nVjIlvac1jOne5wifB8vCtIoktnv37pa+5ZZbute/4IILWpoSXV6XlrxaN7QEUN7M50VpPi0RixpV\nZCyqzypLVU9mqaxKrGfaJxh5jhJmFe0lYzMhzIftiGWo+TByV2b8UFFolJWNaVW/mYhZpLZNJTtW\nERIUyrahojpkbFyKmo+S1atocpnrL2q0EaLsMRmrHdt9PZ+fY3tSUbrGSrRV9CfVBpUEm/ND7ZMq\nYh3vk9fnGE+7Ry/KUMTKeVZZCRUqwkdNqzl2NW10bMSZDL2yqyhwKgqKarOLauMibEdqrjxSi0Gm\nfxPWP63wn/zkJ1uaFubNmze3NG38bPcZ24aa3yvsX+94xzta+sEHH2zp6667rqXZpjJ2KabZf2kr\ne/Ob39zStJj12qyaK9X4lZmTVN2pPsDxjHAM65VnrD1Una/uaZFQFhoVQVFZhHptQD031afVfECU\ndV7Z9BRjbL6ZSGaZcZp5c0ykRVpFylPfQ1m2Wjfqu5laZ2QiyRK1tQmfB8vAdZKKGlqP8zlmrGlj\n3n9kscLHGGOMMcYYY4wxZsnwCx9jjDHGGGOMMcaYJWNNROnKMCZKRkYax/woIaV1i7Yo5kPrB9OM\nJKJ22e9FWVE2CWV5ykgVVR0oi5Kyxajzq6ye0jhGPqE0jvAZsIwqKswdd9zR0pQAU3bMaFuMVMb6\no8S5PidG+qI1T0kuM5EZlgEl81W79St7xrxID2rne8o9aVNU9gwlz2S7V3Yw9tmeLJTtkvmpKAZE\n1Qvvm/JQZWNSloB5FoLVyEDVmJWJssMyqjqbdy0lpc9I/FUdcSxbVNSzGBshqfYH9gvVp9QzJ2rM\nUOOBGhv47NT8VPsk+y77Ke+Jz5x9TVkjlNUrExFEWVt70X0ydZG5piJjvxlbhprORNfkWKrGyozd\nfq2jIsIpaw/rRc0bvXWhsv6q9dT+/ftb+n3ve1/3fNonNm7c2NLbtm1r6csuu6ylX/nKV7Y07Q68\nbm0jXBezb7IP0mb18Y9/vKVrxCnmN4uykbFfs+yXX3559/zeHM36VdtDqK0RlIVGjWsqApOysrP+\nXv3qV7f0O9/5zoiIeO9739u9prKNqvl0GazQypakttjIzGG9yLNqTFMR9NiXlfVV5aPampqXe1sA\nqHUp60WNx7wO6479nWt2fjc788wzW5r2LsK64XeCel21JQTPZVlURC3Vx/lZll1Z1rjlg3pf0FuP\nE9WWvibRzo5KLsYYY4wxxhhjjDFmzeAXPsYYY4wxxhhjjDFLxsJYukjPMkBZqYpuQHgOozU99NBD\nLc2IBhmZJ6WXREny6mdZRlq3KBGj/UhZt5Ssn9I7JdunzJSRDihxY/7V+sYoR5QIU25HKFVV9037\n1Z133tk9nxJkyot5f3xOlOHVa/H5bt26tVteFXmEz0C1sUVlrBVonvVBSYiVJFTJ5Nm+KAllv2N/\npNyyF6EoYmW7J/U+VB9hu1BSTSU7V5aunjR+FmWv6aUztix1H8qW1ZOqHu5azJ/1xzL02ofqa0qW\nS5Y5gl4melvmWdf+oJ7/2IiaysJEmI+Sz6u2w/ZVrVyce1Rf5+dUO2I6E9UjI3dX9o/e31UeygJJ\nVHvIRIVRtj21luqVZ5495nAsgxVaWYKVpZ91qNpdD2XfyNSzmre45uIamJFRuR7esWNHSzPSFT/L\n9V2vjKwvbgFw0UUXtfQ999zT0srioPLn2vX8889vaa4R1Vq+5q/mQRVtlvdP+xrLwnVpps+SzPhU\nI67xPrmOVtGdxkbRXAYy2w7M27Lgaz12qfEjsx5XdsMK70fZojLfAdh/uTZX9iqu6/lZVbZeFC4e\nU1ZsXjOz3UTm+zG/b6j6Zd+fV+8ZvhZ90wofY4wxxhhjjDHGmCXDL3yMMcYYY4wxxhhjlozjZunK\nSJQyEvN5ka4ykSMOHDjQ0vfdd19L00bFHcb5WUb1UpIuXrdn/+nJ1SNWRlqgbPSss87q5kfprtp5\nnJI1nq+sLZSyMc96r5Twsl7UDvnKbsB89u7d29KMzEU5H6NqUUKorCDr1q1r6VrffF6sd1XesZK8\nZUPZBFSkg/p8lTRRySr5PJUUmW2a8mq2Y8qxKV1V7b5n31Ny/NVEsVD2LmV5yVh0eK/1nEy/y0TN\nGStfVuOvSpNaH73oEhG56E7LEGGEcByjdJnjF2H90/bEflLPyUSMUc+CqMiOfF7KspiJwMn2Uu+b\ncyLHb6ZZX8pSqKKTKPuislrxHDUO1c+q6KFqHZOxayk5vLILqf7I59GLdKik9MqKq9YFZFHtJMr+\npiyD6pzeGkatydT159kIDwfrn+PEbbfd1tK33HJLS19zzTUtzTVlXcepeY150wby9re/vaXvvvvu\nllb2LmXDOOecc1p6586dLa2iIfUsbr1tFyJW9guuSz/5yU+29AMPPNDSKqLWVVdd1dK0YI2NzMmx\nuK7TN23a1I7x+4uawzO2oEXtm2uVsespZRVWbWEeai7J2MUz2zMoexXTtHSpeasXQVR911D3QTJb\nUrBOWV51PvM8ePBg9/x5ZCJzqTXS2LZ0Yn+DNcYYY4wxxhhjjFlC/MLHGGOMMcYYY4wxZsk4ppau\n1ew6raRsVZLJiAM8l7JYSr14nLvZ79mzp3sObVSUmlHGpSR2lI325PGUpvGalKbz/nq7l89eR8nt\nMrYRpim9611LyWPVs1bRkmg94DOgLHXbtm0tffrpp3fvg2WgTHrDhg2HlOfhhx9ux1jXfAaZaCfL\ngJIPKvuR2v2en63PgnY9ZaFSUWuUNUFFSWN52aaIsnb07EJKmk+U5UVZizLRAlSdknkyTyULVyh7\nF1H9QdlAOG6x7ytbTJXusu9SGq/kumr8Us9jkVB2R1Uv7G+qDdT02EhQqv4zEYfm9bUsNR9l5WT7\nU3OfshQquyfrXfWNMdHvMrZKFSFSWT+UXTYTeWze+iri+fpmXajIicqGQPtNJlrOWmdeNJ8ILcFn\nPV544YUtfe2110bEyjUJ4dqHayWuZwjXULfffntLMwosx2neB/vJF77whZbmupdtoPY3tb6nTYLt\n8rLLLmtpWrG4xYKaE7k2v/rqq1v60ksvbWllhWW6lo1jBtsu1xO0cf3RH/1RS3PM4DVZH9u3b+/e\nh7LRsDx8Tr11D7eeUPU1L4rT7PFF7Ztq7abuWZ0zxh7J55axWGbszJl1S8bGPu8+1NzD42o9peYb\njveZtbyyatb8Vf1m1oVE1RevqWxiKvLs0fh+mLF0ZSK1KRazJxtjjDHGGGOMMcYYiV/4GGOMMcYY\nY4wxxiwZx9SjonbZV7IrJSXsSadVHrwmJZCM8EF5KmWbLCNlqyqqFs8hlJ73pGwqgpCyX2WkZsoe\nwvwz0j/eE+VutWy8TkYiTgktz2c9MkoX65qRthjdQNlJKB+mDLpel9HZGG2NbWD9+vUxj2WIBJSR\n/yqrhopqUds9n7mqZyUhzUSeYVpF31FySxUJpV5X7dSv5KxKCqwk0mqMy1he58mBj1TaO3uOkper\nOuUzUFYbZbuqeXKsyVi6MpEOliHaSKb+VT+dh4rSodqoatMqqsdYm4A6p953xlaq0ipKlrKK9mwr\nETkbVy+trHbML7MuUnZZFXVLrSNURLAeymKoxkrmTZsL+zjzWSRYV5lIgaoP7Nq1q6Xf9a53HXId\nzqG02StbPJ8FI0f93M/9XEt//OMfH3Ufaizt3VPG/sy+xmvu2LGjpVUkObYjzg+0/bN9KRsGI+HW\n9cq5557bvc4dd9zR0jfccENLc02jIv7w/hhhllsNKDuLWt/we0UtA++fY5aKUkaWLSJtxtKl5q15\nazq15iUZW5j6nqQsXZmoaqRXB8oSzHaRmdfUXJWxqWXutXdPamxStuixVje1bYWqjzFtSW2VQcZG\nL89Y8sni92pjjDHGGGOMMcYYswK/8DHGGGOMMcYYY4xZMo5b2CHKn5RMLSNv6kmaKA+mFJYSSKZp\nJ+I1KaukhYgSUmXp6llbZvOv8jFlmVCSZyVHp7z71FNPbWll+8rsSE5pMI/znirKSsByKQkaj1Oa\nzDo9++yzW5r3R5T8sGfvUtJ4RkJQMkAlaV5mlMyX/ZfPsdajsk+qKCFMqzbKsrA/qihtKh8lP50n\naVa2lYy9K2OXyUQtm2e74r0pK1AmMgivqWxyajxXEnQlb63XYn/tRWuYzUNJhI802sYikLFFq3G9\nHlfW30w9q4gdmQhvCtU3ejYiFbEs85w53nPMIFu2bDns9WfzUffda5sZq0zGVqH6l4pgpvLPrEHq\nOepcFc2NfZl1p9KLxNiIR6oPsJ5756roNHyGrENGTNu8eXNL09qubMnKZqLW6b12mrGYqHGaZWS/\nZptmPlwj8l5Zf5nooPX++J2Bf7/55ptbmvYuZclkmtYxroEYkUxZUZgP2wHrpqbHjoNE2WIzET4X\nlYxduXf8aEX8HGtLOhqoeVWtBVYzJ7GvKVtlZryp5cmsnXn9zBYLah1LlAVLPZve94NMpLbMcTLW\nemmFjzHGGGOMMcYYY8yScUwVPurXDfX2TME3hfUXYfVrozpO1QFVOtwYeNOmTS3NjfL4Fp2/Xqlf\n1PkGk9eqn80obfgrO+9fXZOoN7R845jZ4LanLlBvU1lGKpLUL1VqIyyqerjZHcuifqlU912fJfPj\nry781VapKJZhA1iifnHO/ILJ58v2XZVa7GuPPvpoS/M43/jzlzy1kR43U+Sz4HH2TbVZqFLq9BQQ\nhO0vs4EzUWoU9Wu9UlWwz/Y2sWb/Ur++q1941K/8GcWV6vu8PzVG1+fE56X6utoUkyyDqkf9IqcU\nlWoT4t7zVXmoZ6vabmajRJWP+tVOtfXar6loyKiHOMZQRUpFoVJ9EpZF/fo+bzNMVXdjlaN8fry+\nuleOz+zLah3BOq5l5/2o8Y559JQIs9dfBoVPRt2pxt7eeiIzD6uNU5WqWs1bCp7DMVmpZHu/xKv8\n1HHVr9VGuVybs4yqTXPdx2vVeUs9F44TKm/Od5wHqWbmWrN3/dnrZlQNtV1Rlci+xrKreZgsg8In\no6oeG5zgSBU+Y8f1jHo5o7ibt2mz2hw8oxxRa3Oi5kGlqlX11AtwlBkfx254rcbqzLpeUfNRa6TM\nhtf8rCpjBit8jDHGGGOMMcYYY5YMv/AxxhhjjDHGGGOMWTKO26bNlCspWbnaJJiyyd4GpU8++WRL\nq42w9u3b19KUv55//vndNKWXLBc3x+Nmb5SW8nxu3lbPoayOkjVCGZeSmnNjaWWrYP4sF++Pz6NX\n1xErN8rrweelLAaqjCzLtm3busdV2ZWFj3LCWgdnnnlmO0arkdpYWkn/lORymeF98jn2NkOndUul\n+TnWP59tZnNTZUXJWJfYBnuyTSXJVNLPjCxaWcqUbVPZuHob2PasrxG5jfqULFht4KysmkrGqzYe\nrflnrGOKjOx5kVD1r6wPrFtloanH1Vin5mRlvWU+6tkqS5dC2QqrpUvZrJXNifPz008/3dKcT2kD\nVWNSxmKnrB01z7Eb46q5R21Mz3zUZs6qP6pnU+tJtRk1DqrxJmMJWOuouV9ZAFjPyu7aQ+Wn5kQ1\nJ7OtZ+yZ7FdcX3L91xv7MxuUMp0Z19Tcqqzbak7icd5HfR6sO2WNy9hA1PjIsWc1dqle/+H3EdYF\nbZ0kYzUaaxtZK2TWM6sJvtFD9UeSsUJnLF0ZG3XvntSaT5UxYz9S9ZsZBzL9p85typKa+W6W6Wtq\nTlJriszcfbQtkav5vrmYs6wxxhhjjDHGGGOMkfiFjzHGGGOMMcYYY8yScUwtXUqCpY6rz/boRcKI\nWCmn4u74lDgqe9Cpp57a0pRHMn8l6WZ5KQtlupZN5UGpKstFOxqjbqhIF8raofKnlI2yY1I/S5mv\nkm4re0pmt3NKblleJeFXu78rSX6vvETZE8iJYuNSVh1l26kWCrZRRovgcWWfOP3001s6Y89Rz2Ls\nuFLPV/LXjKUsI51VkeqUZYxkLBS9c9XnVKQ+JbMlSjqbscH1rEbKLpaRXS8bKiKMsjv07H0RK8fJ\nWucc35VsmWTGACVhzoyfmX5Vy875gGllB+S9Mp2JJKKszSQTraemVX2p8Us9G9UfMhZWNc9zjUIb\nHMfo3vUVmYhNixoJaOzcr+wRjKpWj6s+mIlIk4nKqMZpNT+sX79+bj69KF3KqqIi3Kk5UVm91f1l\nrG+9MUzVS+8ZRWiLkCoXj6t1qSrvPEsL1+P8/vLwww8fcu4sGTvpsqEiC2bWPGMYGxEvE5lLjf1E\ntceKmu9UH8kcz1hL1Rytov/VfNgf1fNS42bGbpdhrB17LWGFjzHGGGOMMcYYY8yS4Rc+xhhjjDHG\nGGOMMUvGcYvSRZQUKiMxrFIv2kMoNaMM86GHHmppWrpoG6EEXsnhKU3jOZSZcid+RuZiOWvZlRyP\nMnXKM3fv3t3Sjz/+eEsr+wSPq6geSkZLCw7PqWVjVACWl8+AZeHzoPSO9asktZTPZZ6Nkq/Xc9S5\nLJeK3LSoUUUyKOuSklcrmXZ91mxDrHO2BVoHSCaSx2rGD6bZpuqYQCunkq1yLGE7Yp9lRCG2KUaH\nYz0xH/YxnqMsGfW+1VjGzzHvM844o6VVNCZ+ltEQVRQQ5pOpm3qcVk5lVVXW2ozlZZFQ9gE+U2Wp\n4xjPeqxjdWZuUDJukrF0ZaLjZSxd9b7ZN9mO2XYyMmtlYVGWtUwEE94Tx7naH5S9LGOBzEQiVHZt\nFY2T6xL2a45Pvc8xnbFYZiyBi4SKcqTsRMo6RctNHUtpz1GWQmW57/WXiJV9Rtmy+Bx5/saNG7vX\n6ln9lO2RqKiUKnonUXY4ZYvO9NleuXq2ktnjyoqltopgnZJMVLF5EZjUuZntNNRYuajzphqPMhG4\njtQurtaIqs4znyWZ9Yxqj/Wzar5Tn1PR6dQcx7Rar/a+S0bocaNXdvajzPeBTJ1mrGnqXufZkjM2\nsq91xOfF7MnGGGOMMcYYY4wxRuIXPsYYY4wxxhhjjDFLxjG1dKkdtjPyOSU9rJJPSpL5d8qTlGmY\nQQAAIABJREFU9+7d29KUYlECThktpWbq+pTLUvZ14MCBlt6zZ0/3nqokjrJV5k2ZmoqQQLsYbTGs\nR9a7snZQtkepHiV5lNNVGwal/yryjoqcRVgWStloWTvrrLNampYQJUtUUYdqm2A0ErXL+9id1xdh\np/YjRdkN5kVuUjJFFSGANoFedJ7ZtIouoGSYykLBa9W+xzFASSw59hDmpyTo7PtKvq6sbPPsJxlZ\nPfOmtYr1q+wstK1ynGV74PjBfNg3e7Yj1XdVm1FjwNdaIns8UXYeZeliurZr1okay5WtIROxg6zG\n0kVqOSnpVvYulle1uXkRHGfPUW2KbV318Xo8Y+MifB7Kzqwk7jxHjdUsD/s11xT1mbHuOGaoNR1R\ntjdlTVrrKBk/75PPTvUfrk3renHdunXtmJpLVN9hO+Lz2rlzZ0uzHXEtRM4888yW5vprXmS5XuSu\nWdScyLUz+44a19le1ZqOqLXLPMuLOq6+GzBvNT5lyqXmtl7bU5EFM9+r1Ni7qGta1WeUhScTXbSX\nB8lEtyRqa4TVRCBVZaj1oSI1M63m/9537wgdfVdZwHi+Wnf0yq7W/axH3oeah1R0NhUljPfKOVFt\nJdMbNzLrDMXY6NYKK3yMMcYYY4wxxhhjlgy/8DHGGGOMMcYYY4xZMo6ppUtJwzK7ppOebYOSUH7u\nsccea2nanyh5pmyV9i5CSZeSdzNSDaMusAyUxVYoQ1VRgzZs2NAt7759+1qatgpawNTO/ZkdySlF\npCy1yubGSj+Zt7KyUfrHety8eXNLsz6UtUPZHGpbYZvhuUoCryTFiyp5Vag2oiLFKHlkra9MtAiV\nNyWcyuajnkXvmUdo+0DPNsFrqsgFql3wmhwbaINg/srexXpifcyLlpMZb1W98zjvieViPfL+1JhI\nKSzHkl6fVX1QjVknio2LKCmyss71xm9lO1B2wEx0Pta5ihbE56uYZw1T96Yi4lHqzX5ElH2CcFzh\n3E15NyXrPasXy6UiVKk+yDrtRbiLWHmvRFm3VfTEnuWVdc31kor6qfqmiti1SHAdqSwhCp5DS9f7\n3//+iFj5PFnPfG5sf+xTjK7GZ7tp06aWPvvss1v6zjvvbGne07nnntvSW7dubWkVuac35ys7De+f\n8wS3QFBRHnmctv+DBw+2tLKHkN53DB6j/YprarZ1tZ7g+MR8GBWYZCIBzouqRXsb61SttVS/U89s\nkVDjGO+HfSaz1qx9ST0ftksV6TQTcVFZ85QVmKjvcr35NBPRVK0XVTtilD3Ofaqu1TzXs6VyHGQ/\nYoRZHudclVl/qG0g+N1aWZ5VtMBKxsaltiRR5c3MMyvyH3W2McYYY4wxxhhjjFnz+IWPMcYYY4wx\nxhhjzJJxTC1dRO0OT8bspq52A3/kkUdamtYqylMpo6L8lfJQSreUVYT2KtrHWDZauqo8jXI4FXWD\nNi7K1x566KGW5v1Rrsv8lfWNEjtK1lgeyulqWlmxeE21w7mSPzJPPj/1DJR8nPC+qwyaxyi5zewa\nv8xkokUo62XvnHky5MPlx2dBqSbljup8JT+ljJbWB0boq/2N11RyTxWli+VSn1X9h2TulTL8nh2H\nz0VZwVQ0MCWlV5F92B8p6VXtiteq/ZBjjbKEjI10sAyo/qOsUypdrUDsF+wLGcuVQsmSmT+PHynK\nhqsiUSqJtIqOp6LyEPYHFS2IfaD2mYw0X0npM1Y29in2NWXp4pikbB617alyEbWmUzbAsdL0tYKy\nnqr5RqXJPffcExEr2+WWLVtamm2Lz5/zgVorXXrppS39oz/6oy194403tjTbK89n+2L+bEf1npQ9\nWNlf7r///pa+5ZZbWlpZPHicUb3uvffeln7d617X0pmoWr1zOWYxwhmPc/5XFhKu2VmPvH4mqti8\nrQSUhVrlrdZdy7BlAetCjd8cJ1XEqt4aRm1NwbSyI6poxiqaH/v7PIvWbBl6djBlpVWWQo5xah5S\nli619QHrXd13L3Iv1+MbN25sabZRtY7lddT6hs+a7YcWWb4X4JzPNOfTet+qvtS2GaqdkEwEbHLi\nrZiNMcYYY4wxxhhjlhy/8DHGGGOMMcYYY4xZMo6bpUtFUhkrBa4yRErmKCl74IEHWpr2J8qrdu/e\n3dK0YlH2pXZ5V9ECyI4dO1qaVqtqIaH0UkU8ouVo3bp1LX3fffe1NCNaXXzxxd18KPdTsmNKCHnf\nLEOVPPJzKkISn5eKAKYsHpTS9WxZs6joPz25Ha+vduXvRT+K0DLXRZW/rgZl9eqRiT6h8ibqfCWJ\nVNYOnkPZdU2zr7G9cIxh26KElnXBfkfZqJKwss9QzqnsaL1zlFxc2V/Yd5jmZ5V8mVEMCOuDz4Dl\n7UVe4DElNR/T7pYFNT9mLCR8pnUs5+dY58pylemnvGbPrjd7XEXx47327D8Z66nq6yRjKR9ra2Qf\n7/UZZaFSc5JKqz5L2wj7mrJ3qX7dO0et15RNTUV0WoZoeio6Xgaez3zq1gAPPvhgO8b1HKN3qfmR\n9mS1zrrwwgtb+h3veEdLq+ipXHOpNlLTajxgv2A0rj/+4z9u6bvuuqtbXjX2c939+c9/vqXf8pa3\ntDTHtkxUvAr76eWXX97S1157bUt/+MMfbmn2wfPPP7+lr7rqqpbmOmNsNCy1lUEtJ9sM+2MmOp5a\nvy/btgaZ757K6lTT6u8Ze67qG2rtqtpF5jtIr72oiK2ZCJWZOlJzG+9JjUk8zvZb16xqvaLmnsz3\nMWUzVRE4Od7wewC/x/euq9papryq34+dc6zwMcYYY4wxxhhjjFky/MLHGGOMMcYYY4wxZsk4ppYu\nFU1JyXkzMqYqgaIUirtoc/d/Wroo3VJ2BGUzokSaUi+ef9FFF7X0hg0bWppRuqpMTUnwWEbKuBlh\n7HOf+1xL1+gOERHnnXdeS9OWQkkcpXeUptEaxvujTLxKV2kPUVJBJUfn9Zn3+vXrW5rPjM+VEclo\nbVFWEMrzavthWfg5Ja3kvapd1heVjHVKyY+VnaKmlSRV2buYB9sIn7myS7Ev85kzHxWBoGeRUu2C\nfZNjg7I4sFzKfqOkwTyHUn32mZ71UNXpPJtPxEp7CuE9sX45fhAl6WXf43VrfbOMqn2dKPCelWRc\n1ZGyV9XnznOVDUhFE1LtmJ9lniqtLMfKxl3PURFLlPVDtR11XN0fUdH3mOY91ePKvknUNdl3eK88\nTtsPI5vwuIo2yr7Pfl3PUVJ+3qdau5GxEUbWInxGnCtUJEai7BF1zXrDDTe0Y1/3dV/X0hzrVXRT\n9YzUWMLPqmh2KmJlb42gni3XwrRGcCsFRqRVNnplhb777rtbmls1MNqY2mKgZ4VmHXHt/j3f8z0t\nzWhgnBPPOeecbprjo7K1q8hmhPdR10aMUqaegVq7LsM6lqgIeiqacC+iVUS/ravnxuvw+spmrWzD\n6juTmpMyc1s9X211oMqrbJW9SFQR2vKsrIHqO+S8LR/Ud5BMOhP5Tt0HrVv8fqy2L6j5Z2yAqoyq\nLCp6l+LEWz0bY4wxxhhjjDHGLDl+4WOMMcYYY4wxxhizZKyJKF1EybjU+VUapWwdjApASdlTTz11\nSB6zacqrlBydsrZetJmIvo0r4nkpl9qxW+2Uz0hflIpSInvbbbe1NKMx0N7FuqGNi9YZ3t/GjRtb\nutpfWEcZqSBtBUqCvGXLlpZmJAc+M0qAKRMmyl5Tj/csarP3RJTEfhkicynp9LzoeBHzozhkdqFX\n0mJKJhmBgtdkudj3aU1QEnS2R9qlqvWBxyitZd+hJUn1ZRWlS0ns2WcythhKO+tnlbVFWW6UxZLn\nqz7O+1M2GhWxiela7zw3I2/PzBWL2k9VVMixdiVaFmtdKFsrx0Ml71YWPdW+OCcyzc/2rLcR/f6j\nLJsc65WUXpWXx5XtnNdlX+ZYxeM8v5ZNWVIyUV5UBDU+X0YC4pzPeqc0nfX3yCOPtDSjZM67voqw\noiTzKtLTIsHnzDGLZGyYvfnvL/7iL9qxv/zLv2zpt73tbS3NtqXmULVuUTYXzpu0ADIfNafXPJk3\n64hruM9+9rMtzbmdqEiMqi9z/uca8fWvf31Lq0iaPUuXsseyH3F9zXasopqpNJ+ZsmqwbOyzdesD\nWtqULVyNa5lIXotEJuqZGptUPvPyzLRXFQU4E5VRzVWZ7yb1XjlPZNK9+Yv5Rei1rrI5qTKqdVyt\nJ2Vdn7etxOw56jqq3SuLn/q+3mtXarsWnss1Vea9wFhbtBU+xhhjjDHGGGOMMUuGX/gYY4wxxhhj\njDHGLBnHzdI1bwfuw53fk11RckWpI6XNF1988SGfi9BSdrV7Nm0elF1R0rtjx45uGVi2KpVTEksV\nOYHXv+KKK1r685//fEtT2qksJ5R0U8bNyBysG0rDq+SP9cgyKokdJWs8h1JFRunatm1bSzMCAaN3\nsT4ocVNy+/pcla1EtTVlbcjYSRYJdW+qP8zLJyO9VHJIttEDBw60NNsRP6tsFUouzYggmzdvbuka\nCU/ZBVkuytRV/1V2B4WS+rI/Mk3rTD1fyWmVxZJjn4ryo+wyqt3zOTF/5snxsaZ5fRWtIBPpkWTa\n7FqE96ki7pCxEbsqSi7ONKXeGQk6z1eRLpVlT0Xsqv1aRYVSNlQVnY4oK1tmXqEVRkWzq2kVKUfZ\n5NRxzn2sA85nvCd+VlleeX9cr9T6UM+a9cX7z0QhzYyJaxHeD+stE8VHpWs9PvDAA+3Yr/zKr7Q0\no7Tu2rWrpdkfmJ/qG5wH2AaZD1EW4d45vD7b+sc+9rGWvu6661qa609lEVfHeU/79u1r6TvuuKNb\ndvaH3rPhMWWV4T2xHpWdVc3/6nuL6ieqvdWtD9R6PHMf82x6i4ZaIxK1NlX33FvTsm6VHZBtRLWX\nTDozJ5BeP2X7Z5pzNdsu5y/Vr9lGVd2peUCNK716ytQFYd5qWwfVv8Za/DL33TtXfX8cu+1NBit8\njDHGGGOMMcYYY5YMv/AxxhhjjDHGGGOMWTKOqaWLEiUlaVLM21Wb0kjKu84777yWpkyN+dFeQLks\nbRtM025AWRklbueee25LUypHuWyVkjE/VUcqOs4rX/nKlqbNiREKaNHKSMmZpt2CVqsqreP9ZHYY\nJ+r6tKowItnu3btbWkVZU9FRKF+vz0PZWdRO7WOlfItEZjd7ZRFSdVH7Bvsdn20mWhVlzkRJSJVN\ngPnTmkjL4Pbt21u6tjsV1YbRa3h/PEdFoWG7VNJpZbtSkeU4xtS+xLzZvyhB5udYX8ybtjc1fijp\nLKEcl/n3rJW8ZxWJJhOlKhOFY62TkfkSPl81b9TjSl7OeU3J0ZVlQFl++NlMVBElta5jgopwo6Tb\nrAu2exXJjP2R1i1Gw2SaEYJYhl60MdVHWMZMvXP8UhGj2K+5FmCa86OKrFfHHo7htJRxbFLPTkU+\nYR9fJFT0FGWt4XMkvfUX6/7mm29u6Xe/+90t/b3f+70tzS0LeB21DuK4y/KyLCyDWo/2Is4xv/vv\nv7+l//zP/7yluUZVEctU9FBlCWE+jGz2hS98oaWvueaaluY6sn5WRe3NWGvHWPYi9Jikxg/2GVrW\nGNGtwn6q2qO6JxVVaplRNq3eHKq+6xC15lrNcZVW9O4pY7/m+oztiPlxba6+y3FNoeZiNef11qks\nI89VdZGxLKqxhKgy8v7UXNAj831r7GczWOFjjDHGGGOMMcYYs2T4hY8xxhhjjDHGGGPMknFMtXpK\nnknZFVHHKUOj1LqyZcuWlt60aVNLK7k28zvrrLO6ZaR8XEm6VCSAedK3jG1I1QVlbxdccEFLU2rN\n8vI+KNWjrYx1QEtLT9pJ6Zqys6iIHcrGQ/kc7+OSSy5paSV5ZXtQUYGqlFlJaFlfvegws+U9UZhn\nD5lNVzk4peOUlDOt6pxth3WuLAAqOgml6WxTbOscK+oYwvvhNZWdSMkzOQYoyThRdhn2UxV9R9mb\neudmLF0qzf6g7GvqeSgJcC8PJXNV0v9lsFhmyETpUtbA+lnmoSKDEBUljbC9su/TSkkrlJJmM5/e\n82WfojWDx5UViv2IbU1J0FleRhSitZP9QVlk5tkjlM1J2WloeWYf5LOm1Yw2Llp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AAAAg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\nbK5rblyMX5OKmnuXHXPmFmjzaCuzb2Bc0+mwM4+xY16Ey521jVdjOYLji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jIb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\nZ2cSjplk0cZNbud9WFt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UQN17771Vda1UhX9/+OGH92XGIKVj5sbF+Or0MR33UD6zIRMz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FOkA7KN6PYpmSldP9NPaV5UAq/thGwDWu56rLYrvY/WMya7QcbSlLE57BK9Ubro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\nGV6/do8Dn5N3CPvE0XrvHVV17ZEF8p5pmv7SNE1fODhd3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BBCCCGEEEIIIRwY+cEnhBBC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LZBO4tF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\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HlzQjRFrEH97TLuulSeDNpmAy9ZH8+vhx69dr7byjaCM23pnlinTk8LvGtSq3z43uySxi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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6690482cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['figure.figsize'] = (20.0, 20.0)\n",
    "f, ax = plt.subplots(nrows=5, ncols=5)\n",
    "\n",
    "im_samples = []\n",
    "\n",
    "for row in range(5):\n",
    "    for i, j in enumerate(np.sort(np.random.randint(0, train_labels.shape[0], size=5))):\n",
    "        im = train_dataset[j].reshape((64, 64, 1))\n",
    "        house_num = ''\n",
    "        for k in np.arange(train_labels[j,0]):\n",
    "            house_num += str(train_labels[j,k+1])\n",
    "        house_num += \"--\" + str(j)\n",
    "        im_samples.extend([j])\n",
    "        ax[row, i].axis('off')\n",
    "        ax[row, i].set_title(house_num, loc='center')\n",
    "        ax[row, i].imshow(im[:,:,0], cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class Net(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Net, self).__init__()\n",
    "        self.conv1 = nn.Conv2d(1, 20, 3, padding=(1, 1))\n",
    "        self.bn1 = nn.BatchNorm2d(20)\n",
    "        self.conv2 = nn.Conv2d(20, 40, 3, padding=(1, 1))\n",
    "        self.bn2 = nn.BatchNorm2d(40)\n",
    "        self.conv3 = nn.Conv2d(40, 80, 3, padding=(1, 1))\n",
    "        self.bn3 = nn.BatchNorm2d(80)\n",
    "        self.conv4 = nn.Conv2d(80, 120, 3, padding=(1, 1))\n",
    "        self.bn4 = nn.BatchNorm2d(120)\n",
    "        self.conv5 = nn.Conv2d(120, 160, 3, padding=(1, 1))\n",
    "        self.bn5 = nn.BatchNorm2d(160)\n",
    "        self.conv6 = nn.Conv2d(160, 200, 3, padding=(1, 1))\n",
    "        self.bn6 = nn.BatchNorm2d(200)\n",
    "        self.conv7 = nn.Conv2d(200, 240, 3, padding=(1, 1))\n",
    "        self.bn7 = nn.BatchNorm2d(240)\n",
    "        self.pool = nn.MaxPool2d(2, 2)\n",
    "        self.FC = nn.Linear(960, 1080)\n",
    "        self.bn8 = nn.BatchNorm1d(1080)\n",
    "        self.digitlength = nn.Linear(1080, 7)\n",
    "        self.digit1 = nn.Linear(1080, 10)\n",
    "        self.digit2 = nn.Linear(1080, 10)\n",
    "        self.digit3 = nn.Linear(1080, 10)\n",
    "        self.digit4 = nn.Linear(1080, 10)\n",
    "        self.digit5 = nn.Linear(1080, 10)\n",
    "        \n",
    "        #for m in self.modules():\n",
    "         #   if isinstance(m, nn.Conv2d):\n",
    "          #      init.kaiming_normal(m.weight)\n",
    "           #     m.bias.data.zero_()\n",
    "            #elif isinstance(m, nn.Linear):\n",
    "             #   init.kaiming_normal(m.weight)\n",
    "              #  m.bias.data.zero_()\n",
    "    \n",
    "    def forward(self, x):\n",
    "        x = self.bn1(F.relu(self.conv1(x)))\n",
    "        x = self.pool(self.bn2(F.relu(self.conv2(x))))\n",
    "        x = self.bn3(F.relu(self.conv3(x)))\n",
    "        x = self.pool(self.bn4(F.relu(self.conv4(x))))\n",
    "        x = self.pool(self.bn5(F.relu(self.conv5(x))))\n",
    "        x = self.pool(self.bn6(F.relu(self.conv6(x))))\n",
    "        x = self.pool(self.bn7(F.relu(self.conv7(x))))\n",
    "        x = x.view(-1, 960)\n",
    "        x = self.bn8(F.relu(self.FC(x)))\n",
    "        yl = self.digitlength(x)\n",
    "        y1 = self.digit1(x)\n",
    "        y2 = self.digit2(x)\n",
    "        y3 = self.digit3(x)\n",
    "        y4 = self.digit4(x)\n",
    "        y5 = self.digit5(x)\n",
    "        return [yl, y1, y2, y3, y4, y5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!\n"
     ]
    }
   ],
   "source": [
    "net = Net()\n",
    "f = open('c321_overfit_longer.pkl', 'rb')\n",
    "net.load_state_dict(torch.load(f))\n",
    "f.close()\n",
    "net.cuda()\n",
    "print(\"!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None\n"
     ]
    }
   ],
   "source": [
    "print(list(net.parameters())[0][0].grad)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for param in net.parameters():\n",
    "    if(param.grad is not None):\n",
    "        print(param)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.FloatTensor torch.Size([22152, 1, 64, 64])\n",
      "torch.LongTensor torch.Size([22152, 6])\n"
     ]
    }
   ],
   "source": [
    "data_tensor = torch.from_numpy(train_dataset)\n",
    "target_tensor = torch.from_numpy(train_labels).type(torch.LongTensor)\n",
    "print(data_tensor.type(), data_tensor.size())\n",
    "print(target_tensor.type(), target_tensor.size())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "objective = nn.CrossEntropyLoss()\n",
    "optimizer = optim.Adam(net.parameters())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "22152\n",
      "346\n"
     ]
    }
   ],
   "source": [
    "num_epochs = 100\n",
    "batch_size = 64\n",
    "num_train = data_tensor.size()[0]\n",
    "print(num_train)\n",
    "iter_per_epoch = num_train // batch_size\n",
    "print_every = 150\n",
    "print(iter_per_epoch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "epoch_losses = {i:[] for i in range(num_epochs)}\n",
    "loss_history = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!\n"
     ]
    }
   ],
   "source": [
    "net.train()\n",
    "print(\"!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  3.069216728210449\n",
      "loss3d :  1.11677086353302 loss2d :  1.406378984451294 loss1d :  0.5460668802261353\n",
      "Iteration :  151  /  346\n",
      "loss :  1.267390251159668\n",
      "loss3d :  0.5735924243927002 loss2d :  0.2483816146850586 loss1d :  0.44541627168655396\n",
      "Iteration :  301  /  346\n",
      "loss :  1.9240120649337769\n",
      "loss3d :  0.8116130828857422 loss2d :  0.6791820526123047 loss1d :  0.4332168996334076\n",
      "time taken :  426.8482139110565\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 1/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  1.125109076499939\n",
      "loss3d :  0.6383737921714783 loss2d :  0.2303403913974762 loss1d :  0.2563948333263397\n",
      "Iteration :  151  /  346\n",
      "loss :  0.6175701022148132\n",
      "loss3d :  0.2713724970817566 loss2d :  0.3261811435222626 loss1d :  0.0200165044516325\n",
      "Iteration :  301  /  346\n",
      "loss :  1.254986047744751\n",
      "loss3d :  1.0161548852920532 loss2d :  0.15582428872585297 loss1d :  0.08300687372684479\n",
      "time taken :  427.64610147476196\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 2/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.7278286218643188\n",
      "loss3d :  0.2719426155090332 loss2d :  0.24311506748199463 loss1d :  0.21277093887329102\n",
      "Iteration :  151  /  346\n",
      "loss :  0.4145365059375763\n",
      "loss3d :  0.08409380912780762 loss2d :  0.2761033773422241 loss1d :  0.054339319467544556\n",
      "Iteration :  301  /  346\n",
      "loss :  1.2154299020767212\n",
      "loss3d :  0.7059310674667358 loss2d :  0.21279990673065186 loss1d :  0.2966989278793335\n",
      "time taken :  415.3176975250244\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 3/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.5634540319442749\n",
      "loss3d :  0.3058564066886902 loss2d :  0.1610420048236847 loss1d :  0.09655561298131943\n",
      "Iteration :  151  /  346\n",
      "loss :  0.3182837963104248\n",
      "loss3d :  0.11703334748744965 loss2d :  0.11272474378347397 loss1d :  0.08852572739124298\n",
      "Iteration :  301  /  346\n",
      "loss :  0.7413479685783386\n",
      "loss3d :  0.6472354531288147 loss2d :  0.08839137107133865 loss1d :  0.0057211765088140965\n",
      "time taken :  417.16492104530334\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 4/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.27817562222480774\n",
      "loss3d :  0.17707668244838715 loss2d :  0.011896037496626377 loss1d :  0.0892028957605362\n",
      "Iteration :  151  /  346\n",
      "loss :  0.3180874288082123\n",
      "loss3d :  0.23350781202316284 loss2d :  0.04643232002854347 loss1d :  0.03814730420708656\n",
      "Iteration :  301  /  346\n",
      "loss :  0.7132341861724854\n",
      "loss3d :  0.5403295755386353 loss2d :  0.05928511545062065 loss1d :  0.11361950635910034\n",
      "time taken :  412.8771893978119\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 5/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.8648926019668579\n",
      "loss3d :  0.4565654993057251 loss2d :  0.3429983854293823 loss1d :  0.06532874703407288\n",
      "Iteration :  151  /  346\n",
      "loss :  0.20223140716552734\n",
      "loss3d :  0.059897422790527344 loss2d :  0.11251451820135117 loss1d :  0.029819466173648834\n",
      "Iteration :  301  /  346\n",
      "loss :  0.24497266113758087\n",
      "loss3d :  0.11748205870389938 loss2d :  0.01029199082404375 loss1d :  0.11719861626625061\n",
      "time taken :  418.65511107444763\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 6/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.262253999710083\n",
      "loss3d :  0.0970931351184845 loss2d :  0.09201592206954956 loss1d :  0.07314495742321014\n",
      "Iteration :  151  /  346\n",
      "loss :  0.33834490180015564\n",
      "loss3d :  0.06784118711948395 loss2d :  0.1037537157535553 loss1d :  0.1667499989271164\n",
      "Iteration :  301  /  346\n",
      "loss :  0.36091241240501404\n",
      "loss3d :  0.11819478869438171 loss2d :  0.24125662446022034 loss1d :  0.0014609857462346554\n",
      "time taken :  418.99022459983826\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 7/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.09308981895446777\n",
      "loss3d :  0.02042611502110958 loss2d :  0.06974096596240997 loss1d :  0.0029227358754724264\n",
      "Iteration :  151  /  346\n",
      "loss :  0.19999665021896362\n",
      "loss3d :  0.09047035872936249 loss2d :  0.09805510193109512 loss1d :  0.011471176519989967\n",
      "Iteration :  301  /  346\n",
      "loss :  0.6381523609161377\n",
      "loss3d :  0.5814048051834106 loss2d :  0.042873188853263855 loss1d :  0.013874339871108532\n",
      "time taken :  415.9586625099182\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 8/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.3868423104286194\n",
      "loss3d :  0.042398035526275635 loss2d :  0.3336409628391266 loss1d :  0.010803323239088058\n",
      "Iteration :  151  /  346\n",
      "loss :  0.4904211759567261\n",
      "loss3d :  0.2645914554595947 loss2d :  0.04442228376865387 loss1d :  0.18140746653079987\n",
      "Iteration :  301  /  346\n",
      "loss :  0.8891562223434448\n",
      "loss3d :  0.12440765649080276 loss2d :  0.05294521898031235 loss1d :  0.7118033766746521\n",
      "time taken :  415.47872495651245\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 9/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.12609852850437164\n",
      "loss3d :  0.051208239048719406 loss2d :  0.07473663985729218 loss1d :  0.00015364194405265152\n",
      "Iteration :  151  /  346\n",
      "loss :  0.07505036145448685\n",
      "loss3d :  0.030108511447906494 loss2d :  0.04379992187023163 loss1d :  0.0011419262737035751\n",
      "Iteration :  301  /  346\n",
      "loss :  0.16772790253162384\n",
      "loss3d :  0.05578313395380974 loss2d :  0.09601805359125137 loss1d :  0.01592671312391758\n",
      "time taken :  414.3969225883484\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 10/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.12340275198221207\n",
      "loss3d :  0.011004838161170483 loss2d :  0.1092880517244339 loss1d :  0.0031098637264221907\n",
      "Iteration :  151  /  346\n",
      "loss :  0.12618237733840942\n",
      "loss3d :  0.10746042430400848 loss2d :  0.011734786443412304 loss1d :  0.0069871703162789345\n",
      "Iteration :  301  /  346\n",
      "loss :  0.17485806345939636\n",
      "loss3d :  0.06486640125513077 loss2d :  0.0721166804432869 loss1d :  0.037874989211559296\n",
      "time taken :  414.71141266822815\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 11/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.41770297288894653\n",
      "loss3d :  0.23894748091697693 loss2d :  0.1616976261138916 loss1d :  0.01705785095691681\n",
      "Iteration :  151  /  346\n",
      "loss :  0.3319527804851532\n",
      "loss3d :  0.2349986732006073 loss2d :  0.05244612693786621 loss1d :  0.04450798034667969\n",
      "Iteration :  301  /  346\n",
      "loss :  0.038780584931373596\n",
      "loss3d :  0.005793117452412844 loss2d :  0.02700169011950493 loss1d :  0.0059857782907783985\n",
      "time taken :  415.17628717422485\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 12/99\n",
      "--------------------------------------------------------------------------------------------------------------\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration :  1  /  346\n",
      "loss :  0.14246965944766998\n",
      "loss3d :  0.12396106123924255 loss2d :  0.010860665701329708 loss1d :  0.007647925987839699\n",
      "Iteration :  151  /  346\n",
      "loss :  0.5191720724105835\n",
      "loss3d :  0.41975635290145874 loss2d :  0.06025190278887749 loss1d :  0.03916383907198906\n",
      "Iteration :  301  /  346\n",
      "loss :  0.43157655000686646\n",
      "loss3d :  0.204415425658226 loss2d :  0.0859847217798233 loss1d :  0.14117638766765594\n",
      "time taken :  412.04193210601807\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 13/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.1330897957086563\n",
      "loss3d :  0.05545300617814064 loss2d :  0.07651431113481522 loss1d :  0.0011224746704101562\n",
      "Iteration :  151  /  346\n",
      "loss :  0.15709178149700165\n",
      "loss3d :  0.04762370139360428 loss2d :  0.008406427688896656 loss1d :  0.10106164962053299\n",
      "Iteration :  301  /  346\n",
      "loss :  0.1524401605129242\n",
      "loss3d :  0.0015110174426808953 loss2d :  0.05418514087796211 loss1d :  0.09674399346113205\n",
      "time taken :  410.16117429733276\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 14/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.044353142380714417\n",
      "loss3d :  0.004248731303960085 loss2d :  0.03755134344100952 loss1d :  0.002553069032728672\n",
      "Iteration :  151  /  346\n",
      "loss :  0.14765511453151703\n",
      "loss3d :  0.012469657696783543 loss2d :  0.012944843620061874 loss1d :  0.12224061042070389\n",
      "Iteration :  301  /  346\n",
      "loss :  0.04384884610772133\n",
      "loss3d :  0.017667638137936592 loss2d :  0.024572791531682014 loss1d :  0.0016084171365946531\n",
      "time taken :  411.8442075252533\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 15/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.11662481725215912\n",
      "loss3d :  0.019590949639678 loss2d :  0.09686760604381561 loss1d :  0.00016625721764285117\n",
      "Iteration :  151  /  346\n",
      "loss :  0.03130370378494263\n",
      "loss3d :  0.02776346728205681 loss2d :  0.002150731859728694 loss1d :  0.0013895034790039062\n",
      "Iteration :  301  /  346\n",
      "loss :  0.05737275630235672\n",
      "loss3d :  0.013284736312925816 loss2d :  0.002971456153318286 loss1d :  0.041116561740636826\n",
      "time taken :  411.87997102737427\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 16/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.10059680789709091\n",
      "loss3d :  0.014590797945857048 loss2d :  0.08535078167915344 loss1d :  0.0006552272825501859\n",
      "Iteration :  151  /  346\n",
      "loss :  0.1806531548500061\n",
      "loss3d :  0.004422954749315977 loss2d :  0.032049760222435 loss1d :  0.14418044686317444\n",
      "Iteration :  301  /  346\n",
      "loss :  0.23860450088977814\n",
      "loss3d :  0.01512157917022705 loss2d :  0.018236134201288223 loss1d :  0.20524679124355316\n",
      "time taken :  410.5807318687439\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 17/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.038754720240831375\n",
      "loss3d :  0.004738206043839455 loss2d :  0.001508667366579175 loss1d :  0.032507847994565964\n",
      "Iteration :  151  /  346\n",
      "loss :  0.2961311340332031\n",
      "loss3d :  0.06609190255403519 loss2d :  0.2290802150964737 loss1d :  0.0009590112022124231\n",
      "Iteration :  301  /  346\n",
      "loss :  0.14799994230270386\n",
      "loss3d :  0.11025549471378326 loss2d :  0.03714722394943237 loss1d :  0.0005972281796857715\n",
      "time taken :  414.43537402153015\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 18/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.011806849390268326\n",
      "loss3d :  0.0031145147513598204 loss2d :  0.0021299582440406084 loss1d :  0.00656237592920661\n",
      "Iteration :  151  /  346\n",
      "loss :  0.3846535384654999\n",
      "loss3d :  0.04241297394037247 loss2d :  0.3394884765148163 loss1d :  0.0027520873118191957\n",
      "Iteration :  301  /  346\n",
      "loss :  0.0774892196059227\n",
      "loss3d :  0.0008751021232455969 loss2d :  0.031038474291563034 loss1d :  0.045575644820928574\n",
      "time taken :  458.6728892326355\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 19/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.04415687546133995\n",
      "loss3d :  0.010713081806898117 loss2d :  0.015041589736938477 loss1d :  0.018402203917503357\n",
      "Iteration :  151  /  346\n",
      "loss :  0.20392262935638428\n",
      "loss3d :  0.020790502429008484 loss2d :  0.17922817170619965 loss1d :  0.0039039552211761475\n",
      "Iteration :  301  /  346\n",
      "loss :  0.6913375854492188\n",
      "loss3d :  0.15492700040340424 loss2d :  0.1559944450855255 loss1d :  0.3804161250591278\n",
      "time taken :  469.20678186416626\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 20/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.029370680451393127\n",
      "loss3d :  0.028153937309980392 loss2d :  0.0007136583444662392 loss1d :  0.0005030859028920531\n",
      "Iteration :  151  /  346\n",
      "loss :  0.041122861206531525\n",
      "loss3d :  0.001390743302181363 loss2d :  0.034185659140348434 loss1d :  0.005546456202864647\n",
      "Iteration :  301  /  346\n",
      "loss :  0.16381780803203583\n",
      "loss3d :  0.15751734375953674 loss2d :  0.0003572702407836914 loss1d :  0.005943188443779945\n",
      "time taken :  507.73038053512573\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 21/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.21096155047416687\n",
      "loss3d :  0.13560640811920166 loss2d :  0.03326013684272766 loss1d :  0.042095012962818146\n",
      "Iteration :  151  /  346\n",
      "loss :  0.1539851576089859\n",
      "loss3d :  0.06529993563890457 loss2d :  0.07305403053760529 loss1d :  0.01563117839396\n",
      "Iteration :  301  /  346\n",
      "loss :  0.05864810198545456\n",
      "loss3d :  0.02537369728088379 loss2d :  0.0325314924120903 loss1d :  0.0007429122924804688\n",
      "time taken :  413.48992013931274\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 22/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.22756746411323547\n",
      "loss3d :  0.018824998289346695 loss2d :  0.10008933395147324 loss1d :  0.10865312814712524\n",
      "Iteration :  151  /  346\n",
      "loss :  0.513041079044342\n",
      "loss3d :  0.40475064516067505 loss2d :  0.10751710832118988 loss1d :  0.0007733262609690428\n",
      "Iteration :  301  /  346\n",
      "loss :  0.17295865714550018\n",
      "loss3d :  0.10126382857561111 loss2d :  0.043492067605257034 loss1d :  0.028202759101986885\n",
      "time taken :  405.55661702156067\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 23/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.010338331572711468\n",
      "loss3d :  0.00995390024036169 loss2d :  0.00018389226170256734 loss1d :  0.00020053863408975303\n",
      "Iteration :  151  /  346\n",
      "loss :  0.31886789202690125\n",
      "loss3d :  0.01267037633806467 loss2d :  0.04952045902609825 loss1d :  0.2566770613193512\n",
      "Iteration :  301  /  346\n",
      "loss :  0.011039149947464466\n",
      "loss3d :  0.004742913413792849 loss2d :  0.006273746490478516 loss1d :  2.2490819901577197e-05\n",
      "time taken :  404.77974486351013\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 24/99\n",
      "--------------------------------------------------------------------------------------------------------------\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration :  1  /  346\n",
      "loss :  0.09744269400835037\n",
      "loss3d :  0.029977524653077126 loss2d :  0.06745921075344086 loss1d :  5.9604644775390625e-06\n",
      "Iteration :  151  /  346\n",
      "loss :  0.04737967997789383\n",
      "loss3d :  0.026532888412475586 loss2d :  0.02047588862478733 loss1d :  0.0003709029988385737\n",
      "Iteration :  301  /  346\n",
      "loss :  0.17217515408992767\n",
      "loss3d :  0.019667301326990128 loss2d :  0.14871986210346222 loss1d :  0.003787994384765625\n",
      "time taken :  403.61655354499817\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 25/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  346\n",
      "loss :  0.030580533668398857\n",
      "loss3d :  0.0024018818512558937 loss2d :  0.028107881546020508 loss1d :  7.077057671267539e-05\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-24-badf81dc70b2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     45\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mbin2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     46\u001b[0m             \u001b[0moptimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzero_grad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 47\u001b[0;31m             \u001b[0midxs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLongTensor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbin2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     48\u001b[0m             \u001b[0mY\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mY_batch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0midxs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     49\u001b[0m             \u001b[0mlossl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mobjective\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutputs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0midxs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/sreekar/miniconda3/envs/deep/lib/python3.5/site-packages/torch/_utils.py\u001b[0m in \u001b[0;36m_cuda\u001b[0;34m(self, device, async)\u001b[0m\n\u001b[1;32m     63\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     64\u001b[0m             \u001b[0mnew_type\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 65\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mnew_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0masync\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     66\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     67\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "for epoch in range(num_epochs):  # loop over the dataset multiple times\n",
    "    \n",
    "    print('Epoch {}/{}'.format(epoch, num_epochs - 1))\n",
    "    print('-' * 110)\n",
    "\n",
    "    i = 0\n",
    "    rng_state = torch.get_rng_state()\n",
    "    new_idxs = torch.randperm(num_train)\n",
    "    \n",
    "    t1 = time.time()\n",
    "    for t in range(iter_per_epoch):\n",
    "        batch_idxs = new_idxs[i: i+batch_size]\n",
    "        i += batch_size\n",
    "        X_batch = data_tensor[batch_idxs]\n",
    "        Y_batch = target_tensor[batch_idxs][:,0:4]\n",
    "        lenths = Y_batch[:, 0]\n",
    "        bin3 = []\n",
    "        bin2 = []\n",
    "        bin1 = []\n",
    "        for idx, lenth in enumerate(lenths):\n",
    "            if (lenth == 1):\n",
    "                bin1.append(idx)\n",
    "            elif (lenth == 2):\n",
    "                bin2.append(idx)\n",
    "            elif (lenth == 3):\n",
    "                bin3.append(idx)\n",
    "        \n",
    "\n",
    "        X_batch = Variable(X_batch).cuda()\n",
    "        Y_batch = Variable(Y_batch).cuda()\n",
    "        optimizer.zero_grad()\n",
    "        outputs = net(X_batch)\n",
    "        \n",
    "        if bin3:\n",
    "            idxs = torch.LongTensor(bin3).cuda()\n",
    "            Y = Y_batch[idxs]\n",
    "            lossl = objective(outputs[0][idxs], Y[:, 0])\n",
    "            loss1 = objective(outputs[1][idxs], Y[:, 1])\n",
    "            loss2 = objective(outputs[2][idxs], Y[:, 2])\n",
    "            loss3 = objective(outputs[3][idxs], Y[:, 3])\n",
    "            lossd3 = lossl + loss1 + loss2 + loss3\n",
    "            lossd3.backward(retain_variables=True)\n",
    "            optimizer.step()\n",
    "        \n",
    "        if bin2:\n",
    "            optimizer.zero_grad()\n",
    "            idxs = torch.LongTensor(bin2).cuda()\n",
    "            Y = Y_batch[idxs]\n",
    "            lossl = objective(outputs[0][idxs], Y[:, 0])\n",
    "            loss1 = objective(outputs[1][idxs], Y[:, 1])\n",
    "            loss2 = objective(outputs[2][idxs], Y[:, 2])\n",
    "            lossd2 = lossl + loss1 + loss2\n",
    "            lossd2.backward(retain_variables=True)\n",
    "            optimizer.step()\n",
    "        \n",
    "        if bin1:\n",
    "            optimizer.zero_grad()\n",
    "            idxs = torch.LongTensor(bin1).cuda()\n",
    "            Y = Y_batch[idxs]\n",
    "            lossl = objective(outputs[0][idxs], Y[:, 0])\n",
    "            loss1 = objective(outputs[1][idxs], Y[:, 1])\n",
    "            lossd1 = lossl + loss1\n",
    "            lossd1.backward()\n",
    "            optimizer.step()\n",
    "        \n",
    "        optimizer.step()\n",
    "        final_loss = lossd3 + lossd2 + lossd1\n",
    "        \n",
    "        loss_history.append(final_loss.data[0])\n",
    "        epoch_losses[epoch].append(final_loss.data[0])\n",
    "        \n",
    "        if (t % print_every == 0):\n",
    "            print('Iteration : ', t+1, ' / ', iter_per_epoch)\n",
    "            print('loss : ', final_loss.data[0])\n",
    "            print('loss3d : ', lossd3.data[0], 'loss2d : ', lossd2.data[0], 'loss1d : ', lossd1.data[0])\n",
    "        \n",
    "    t2 = time.time()\n",
    "    print(\"time taken : \", t2-t1)\n",
    "    print('-' * 110)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "f = open(\"what_now.pkl\", \"bw\")\n",
    "torch.save(net.state_dict(), f)\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f7833fe3d68>]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AuBth0T2qzm5DGzmuDQ0AAAC4I2HRY/av3/2heN+HPxkRdx9wLRYCAAAALk1Y9Jj9nR/5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Hr3A69tcZNFrKEBAADgwBAW4SAl3l/+7ZeqLiM/IGoLMpSE33BraFrksauncn2WFZNFiQRhUZIo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\nSOHkci9Om5pzH1ksAr5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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7834db7240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(loss_history)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
